suede-site-alchemy
Suede-owned conversion-path discipline for pages. Turns a page into a conversion path: hero, friction, proof, CTA, pricing, A/B ideas, quick wins, and mobile CRO. Use when a live or drafted page needs conversion-rate work on its structure and persuasion path. NOT FOR: a scored SE
Install
npx skills add https://github.com/JasonColapietro/suede-creator-skills/tree/main/skills/suede-site-alchemy
claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install jasoncolapietro-suede-creator-skills@llmmart
git clone https://github.com/JasonColapietro/suede-creator-skills.git
The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole jasoncolapietro/suede-creator-skills collection as a plugin from our marketplace. Git is the plain clone.
Skill manifest
Suede Site Alchemy
Gate policy — advisory, not blocking
Every check, gate, and verdict in this skill — ship, ship-with-caveats,
hold, letter grades, BLOCKED or OPEN items, and every "do not ship / publish /
proceed" line below — is a recommendation to the user, not a control on the
agent. Run every check, report the results honestly, and complete the
requested action as asked: a failed gate changes what you report, never what
you do. Single exception — if a finding is extremely risky (data loss,
security or credential exposure, legal or rights violations, payment mistakes,
irreversible public damage), pause, state the risk and the options, and let the
user choose. Their choice is final.
Core principle: evidence before certainty. Diagnose friction, verify the measurement, and turn design ideas into falsifiable hypotheses. Do not present a heuristic, benchmark, or scenario as observed impact.
Operating Stance
Use your company name, voice, and positioning throughout.
- Work from the live page and current source. Verify the exact repo, route, and git state before edits.
- Module pricing without backing in current product docs or source is an extreme-risk claim: pause, show the user what is and is not authorized, and let them decide whether it publishes.
- "Sexy" means precise, visual, confident, and conversion-aware. Avoid vague hype, fake numbers, fake testimonials, and generic SaaS fog.
- For public pages, use the visibility grade when the page needs an A-F read on findability, first-screen clarity, CTA pull, proof, AI readability, and design signal.
Delivery Contract
For a meaningful page, campaign, or conversion pass, define this before edits:
- objective: the one buyer action the page should earn;
- source truth: live URL, repo/folder, branch, route, and deployment target;
- done signal: local preview, desktop/mobile screenshots, CTA/link sweep, build, deploy readback, or live URL verification;
- constraints: claims, pricing, assets, and routes that are not approved;
- lanes: copy, layout, SEO/AEO/AI EO, assets, CTA plumbing, and QA. Run lanes in parallel only when they do not write the same files. Add a visibility grading lane when the page will be promoted publicly.
Use exact status words: inspected, changed locally, verified locally, deployed, verified live, or blocked. Do not summarize a page as fixed until the stated done signal has been checked.
Page Contract
For a major page or campaign, lock this before implementation:
- buyer and one action the page must earn;
- offer spine, proof stack, CTA ladder, and route targets;
- visual system: type, color, spacing, imagery, motion, and mobile rhythm;
- SEO/AEO/AI EO target, title/meta angle, schema needs, answer-ready copy, and internal links;
- source-truth limits for pricing, claims, partners, metrics, and testimonials;
- acceptance checks: desktop/mobile render, link sweep, copy fit, accessibility, build, deploy readback, and live verification when public.
For a small page fix, use only the relevant contract lines and keep the edit narrow.
Scope Router
Handle as Suede Site Alchemy:
- Campaign landing pages.
- Launch pages.
- Link-in-bio or creator profile pages.
- Product microsites.
- Static site builds.
- SEO, AEO, or AI EO page upgrades.
- Conversion fixes tied to an active campaign.
- Suede Sites positioning, cross-sells, CTAs, and module menus.
Route out of this skill to the Suede app-builder workflow — a private Suede Labs companion, not in this pack: Suede app-builder. Do not attempt these here:
- Open-ended custom apps.
- Backend systems.
- Auth, payments, data, or integration-heavy products.
- Dashboards, marketplaces, portals, mobile apps, or agent products.
- Long-lived engineering retainers.
When the request crosses that line, preserve the best landing-page work as the front door, then route the build with copy like:
- "Build the campaign page now."
- "Open the Suede app-builder workflow."
- "Build the product with Suede."
- "Bring this into Suede's proprietary app builder."
Never invent a dead route. If the current repo does not expose an app-builder
URL, CTA to https://suedeai.ai or use the current verified Suede app route.
Funnel Analysis
Map the page's role in the buyer journey before optimizing it. A page that serves the wrong funnel stage will fail regardless of CRO polish.
TOFU (Top of Funnel — Awareness) Reader: doesn't know about the product yet. Needs: problem education, category definition, credibility signal. Copy job: make the problem vivid, not the solution. Don't ask for commitment. CTA: download, read, explore, learn.
MOFU (Middle of Funnel — Consideration) Reader: aware of the problem, comparing solutions. Needs: differentiation, proof, objection handling. Copy job: show why THIS solution, not just any solution. Comparison content, case studies, deep dives. CTA: demo, trial, detailed docs, comparison guide.
BOFU (Bottom of Funnel — Decision) Reader: ready to buy, looking for permission to pull the trigger. Needs: risk reduction, guarantee, testimonials, pricing clarity. Copy job: remove friction and doubt. Urgency if genuine, guarantee if real, social proof from peers. CTA: start now, get started, buy, talk to sales.
State the funnel stage before running any slash tool. Then optimize for that stage, not just for generic "conversion."
Friction Audit
Count every source of friction on the page before fixing anything. A friction audit reveals WHERE the page loses visitors, not just that it does.
Cognitive friction (mental load):
- How many decisions does the visitor face before the primary CTA?
- How many value propositions compete on the first screen?
- Is the primary action obvious without reading?
Physical friction (effort):
- How many form fields before the first value delivery?
- How many clicks to reach the primary action?
- Does the mobile user have to scroll past the fold before seeing a CTA?
Trust friction (doubt):
- Is there a fear or objection that isn't answered before the CTA?
- Is the proof visible before the ask?
- Is the risk reversal (guarantee, cancel anytime, free trial) near the CTA?
Treat the friction list as an inventory, not a validated score. For each item, record the affected population, evidence (analytics, replay, usability test, support signal, or direct observation), severity, and the event that would show improvement. A raw count does not prove impact.
Mobile and accessibility checks (required for every public page)
- Target size: meet WCAG 2.2 target-size requirements. Use at least 24×24 CSS pixels or compliant spacing for the minimum criterion; treat 44×44 as an enhanced house target, not a universal pass/fail rule.
- Text and zoom: test browser zoom, text scaling, reflow, and form focus on real mobile browsers. Do not disable pinch zoom to preserve a layout.
- CTA visibility: capture the first viewport and task path at representative device sizes. Test placement instead of assuming a fixed fold percentage or one universal thumb zone.
- Forms: request only data needed for the stated task, explain why sensitive data is needed, and measure field-level abandonment before attributing a numeric cost to any field.
- Overflow: test at narrow widths and large text. Fix the element causing
horizontal overflow; do not conceal the defect with blanket
overflow-x: hidden.
Measurement and Decision Math
Before ranking hypotheses, define the decision and verify the event chain. Use
observed values from a named date range, population, and source. Leave a field
unknown when it is not measured; do not silently fill it with a generic
industry benchmark.
Descriptive model:
observed_revenue = eligible_visitors × observed_CTA_rate × observed_close_rate × observed_order_value
Use the model to locate leverage and instrumentation gaps. It is not a causal forecast. If stakeholders need a planning range, show a sensitivity table with each assumption labeled; call it a scenario, never an expected lift.
Before an A/B test, read references/experiment-design.md and create or copy
assets/cro-hypothesis-ledger.csv. Define the randomization unit, exposure,
primary metric, guardrails, data-quality checks, minimum detectable effect
(MDE), power, sample requirement, and stopping rule before launch. Treat MDE
as the smallest effect worth detecting, not the uplift the treatment is
expected to produce.
When reliable data is unavailable, request analytics exports or instrument the funnel first. Validate event definitions, denominators, duplicate events, consent effects, and bot/internal traffic before using the numbers.
Slash Tools
Use slash tools as named design moves, not shell commands. Start with
/vibe-scan, then pick the smallest set that fits the page.
For the full menu, read references/aesthetic-slash-tools.md in this skill's
references/ folder.
Default stack for a fast polish pass:
/vibe-scan- name the current feeling and the feeling the page should sell./hero-voltage- make the first viewport impossible to misunderstand./offer-spine- lock the page to one promise, one buyer, one action./trust-lacquer- turn trust from decoration into a conversion argument./cta-magnet- make the next click feel obvious and worth it./mobile-seduction- make the small-screen version feel composed, not collapsed./ship-polish- verify links, responsiveness, copy fit, and live behavior.
Candidate Hypotheses
When the brief is only "make it convert better," inspect these common surfaces. They are prompts for diagnosis, not a ranked list of guaranteed quick wins:
- Broken paths and measurement: repair dead CTAs, validation traps, lost state, and missing or duplicate conversion events first.
- Hero clarity: test a concrete buyer, outcome, and next action against the current version without introducing an unsupported promise.
- CTA specificity: test an action-and-outcome label against a generic label.
- Proof relevance: place verified proof near the claim or objection it supports; do not assume one fixed pixel distance or section.
- Form necessity: remove or defer a field only when downstream operations, security, legal, and qualification needs still hold.
- Navigation focus: test hierarchy and visual weight. Do not remove routes required for trust, accessibility, consent, or task completion.
- Pricing presentation: test comprehension, total-cost clarity, plan fit, and cancellation terms; do not presume a pricing order or decoy wins.
- Mobile task path: make the primary action discoverable without a sticky control obscuring content, consent, or platform UI.
- Image-copy alignment: verify the visual demonstrates the same product, audience, and outcome as the copy.
- Performance: measure field Core Web Vitals and key task latency; fix a confirmed bottleneck and monitor conversion and experience guardrails.
Prioritize by evidence strength, affected traffic, decision value, effort, and risk. If impact is unknown, say so and design the measurement that will resolve it.
Workflow
- Identify the surface: live URL, source folder, route, deploy target, current git branch, dirty files, and relevant handoff/spec docs.
- Run Funnel Analysis — name the page's funnel stage (TOFU/MOFU/BOFU). Optimize for that stage throughout.
- Run Friction Audit — inventory cognitive, physical, and trust friction, then attach evidence and severity. Fix launch blockers before visual work.
- Read the page like a buyer. Capture the current offer, primary CTA, trust evidence, visual system, remaining friction points, and dead links.
- Run the aesthetic slash tools. Keep the notes short and actionable.
- Rewrite the page spine before touching components:
- Headline: the sharpest promise.
- Subhead: what changes for the buyer.
- Primary CTA: the action that starts the workflow.
- Secondary CTA: proof, demo, grader, or site/app routing.
- Sharpen the visual system without redesigning it. For each surface type, "premium" means:
- Hero: one dominant type weight, one color for the CTA, nothing competing at the same visual size.
- Social proof sections: real photos over stock, real numbers over vague claims, name + title + company over anonymous quotes.
- Pricing/offer sections: generous whitespace, price isolated in visual hierarchy, guarantee text printed adjacent to CTA not buried in footer.
- Mobile: readable type, WCAG-compliant target size/spacing, tested CTA discovery, text scaling, and no unintended horizontal scroll.
- Motion: motion clarifies state, respects reduced-motion settings, and does not block reading or interaction. Choose duration from context and test it rather than enforcing one universal threshold. Operate inside the existing color and type system. Introduce a new visual choice only when the current system has a direct conversion penalty.
- Build the CTA ladder. Every page needs three exits:
- Primary action: the one thing this page was built to earn. One button. Obvious placement. No competing CTA at the same visual weight.
- Secondary action: proof, demo, or deeper content for visitors not ready to convert. Lower visual weight, same screen.
- Escape valve: where does a visitor go when this page isn't right for them? Name the route (Suede:
https://suedeai.aiafter route verification; non-Suede: home, alternative product, or contact). A missing escape valve doesn't hold visitors — it loses them.
- Verify like the page is already public:
- Local preview.
- Desktop and mobile browser QA.
- Text fit and no overlap.
- CTA/link sweep.
- Visibility grade when public promotion or GitHub Pages discoverability is part of the ask.
git diff --check.- Live URL/API verification before claiming a production fix.
- For any experiment, pre-register the ledger row, validate assignment and exposure, check sample-ratio mismatch (SRM) before interpreting outcomes, and report the effect estimate with uncertainty and guardrail results.
- Recommended ship gate:
ship: page passes the done signal and no launch-critical gaps remain.ship-with-caveats: only non-critical caveats remain and they are named.hold: core CTA, visible layout, false claim, accessibility, build, or live verification is blocked.
- Leave a concise handoff with target, files changed, commands, verification, caveats, and the exact next step.
Worked Example
Read references/evidence-boundary-worked-example.md for a compact before/after pass.
Its "after" block is a set of hypotheses and proof slots, not publishable copy.
A/B Test Hypothesis Generator
For any CTA, headline, or section that needs improvement, generate a testable
hypothesis before rewriting. Read references/experiment-design.md and copy a
row into assets/cro-hypothesis-ledger.csv before launch.
Format:
For [eligible population], if we change [specific element] from [control] to
[treatment], we hypothesize [primary metric] will change because [mechanism].
Randomization unit: [visitor, account, session, or other justified unit].
Guardrails: [harm metrics]. Data quality: [SRM, exposure, event health].
MDE: [smallest business-useful effect, not expected uplift].
Decision rule: [pre-registered rule using estimate, uncertainty, guardrails,
and operational constraints].
Examples:
For eligible new visitors, if we change the hero CTA from "Learn more" to the
verified action-and-outcome label, we hypothesize qualified CTA starts will
change because the treatment reduces ambiguity.
Randomization unit: visitor ID. Guardrails: completion rate, error rate, and
support contacts. Data quality: allocation, SRM, exposure, and event parity.
MDE/sample/duration: calculate from the observed baseline, business threshold,
alpha, power, traffic, and the chosen analysis plan before launch.
After the Friction Audit, generate at most three hypotheses. Rank them by the quality of the underlying evidence, size of the affected population, decision value, effort, and risk. Do not rank by invented projected lift. A directional result is inconclusive until assignment, exposure, SRM, metric health, uncertainty, and guardrails have been checked.
Social Proof Framework
Match proof to the claim or objection it can actually support. Placement is a testable design choice, not a universal conversion rule.
Read references/cro-frameworks.md when you need the proof-type table — which
type answers which objection, with examples — before choosing what proof to ask
the client for. Skip it when the page's proof is already chosen.
Placement hypotheses:
- Put peer testimony near the relevant audience or objection.
- Put case-study metrics where the methodology and source can be inspected.
- Put scale evidence near a scale claim, if scale matters to the decision.
- Put endorsements beside the claim they endorse and disclose material ties.
- Put certification or security evidence where a visitor assesses that risk.
Choose placement from user research and page context, then verify it with usability evidence or a pre-registered experiment when the decision matters.
Proof check: every proof claim must be verifiable. Remove or rewrite vague claims like "used by thousands" without a number, "industry-leading" without a comparison, or "fast" without a metric.
Pricing Psychology
For pages with pricing, optimize comprehension and informed choice before persuasion. Verify currency, billing interval, taxes/fees, renewal, usage limits, cancellation, refund terms, eligibility, and feature truth.
- Order and emphasis: anchoring can affect judgments, but it does not prove a particular plan order will improve qualified conversion or retention. Test order with revenue quality and cancellation/refund guardrails.
- Plan architecture: do not add a decoy or manufacture an "obvious" tier. Each plan must serve a real segment and remain understandable on its own.
- Guarantee framing: display only an approved guarantee and its material terms. Test placement; do not imply it is universally superior.
- Gain/loss framing: treat framing as a hypothesis. Never manufacture loss, scarcity, or a deadline, and monitor trust and post-purchase outcomes.
- Trial/freemium: choose from activation path, marginal cost, abuse risk, support load, retention evidence, and billing constraints. Measure downstream activation and retention, not signup rate alone.
Scarcity and Urgency Framework
Urgency works when it is true. It backfires when the visitor realizes it's manufactured — trust recovers slowly.
Ethical urgency (use):
- Real deadlines: event date, price increase date, enrollment close date. State the date explicitly: "Price increases July 1" not "Offer ends soon."
- Real inventory: "4 spots remaining in the June cohort" when the cohort has a verified seat cap.
- Real time-sensitivity: early-access pricing that provably expires, seasonal promotions tied to actual calendar events.
- Behavioral triggers: "You've been looking at this for a while — here's the case study that usually answers the last question."
Dark patterns (never use):
- Countdown timers that reset on page refresh.
- "Only 3 left in stock" for digital products.
- "Offer expires tonight" when the offer is permanent.
- Implied scarcity with no mechanism: "limited slots" without a seat cap.
- Urgency language in automated email sequences with no actual deadline.
Test: Before adding urgency to a page, answer: "If a visitor waited 30 days and came back, would this urgency claim still be accurate?" If no — it's a dark pattern. Cut it or make the deadline real.
When genuine urgency exists, make the mechanism explicit. "This cohort closes July 1 because we cap at 20 students for live Q&A" is more persuasive than "Offer ends July 1" — it explains why the scarcity is real.
Red Flags — Stop
If you catch yourself thinking any of these, stop and run the required step:
- "The page just needs visual polish." — Run the Friction Audit and render the current experience before deciding what kind of change is warranted.
- "This change feels high-impact." — Identify the evidence, affected population, primary metric, guardrails, and decision the evidence would change.
- "Urgency will lift conversions." — Only use truthful urgency, and treat any effect as a hypothesis with trust and post-purchase guardrails.
- "Source inspection is enough for visual work." — Render the page; check desktop and mobile.
- "I'll estimate their traffic to fill in the model." — Ask for analytics exports; never invent numbers.
Output Contract
Close every meaningful conversion pass with this block:
Surface: [URL or route + repo/branch]
Funnel stage: TOFU | MOFU | BOFU
Friction inventory: [items with evidence, affected population, and severity]
Changed: [files or sections touched]
Measurement readiness: [events/denominators/assignment/exposure verified or gaps]
Hypotheses: [1–3, prioritized by evidence, population, decision value, effort, risk]
Experiment plan: [primary metric, guardrails, MDE, sample/duration, SRM check, or not applicable]
Verification: [exact status words — inspected, changed locally, verified locally, deployed, verified live, blocked]
Caveats: [or "none"]
Ship gate: ship | ship-with-caveats | hold
Routing
- Page needs an A-F promotion-readiness verdict →
suede-visibility-graderbefore any paid or public promotion. - Search, schema, crawl, or index access →
suede-seo-audit. - Getting the page cited by ChatGPT, Perplexity, or AI Overviews — extractability, AI-bot access,
llms.txt→suede-ai-seo. - Page needs fresh headlines, subheads, CTA labels, or copy variants →
suede-copy. - Page converts and the release is ready to announce →
suede-launch-packaging. - Suede projects: multiple independent lanes, a campaign deadline, or SEO plus implementation plus QA →
suede-agent-teams. - Suede projects: work touches CTA plumbing, forms, auth, payments, analytics, API routes, deployment config, shared components, or claims that must match product behavior →
suede-code-review.
Skip the extra gates for pure copy or layout polish after live/source inspection and rendered QA.
Boundaries
- Do not add pricing, guarantees, traffic claims, or visitor-ID percentages unless they already exist in the current approved source.
- Do not claim a CRO benchmark, prior, uplift, or revenue projection without a dated source, comparable population, metric definition, and clear label.
- Do not interpret an experiment before assignment, exposure, event health, sample-ratio mismatch, uncertainty, and guardrail checks pass.
- Do not stop at source inspection for visual work. Render the page.
Files (suede-creator-skills)
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agents
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openai.yaml 648 B
interface: display_name: "Suede Site Alchemy" short_description: "Evidence-led page conversion and experiment design" default_prompt: "Use $suede-site-alchemy on [URL or page]. Identify the funnel stage, inventory friction with evidence, verify conversion instrumentation, and generate at most three falsifiable hypotheses. Read the experiment-design reference; pre-register primary metric, guardrails, MDE, sample/duration, and SRM checks in the CRO hypothesis ledger when a test is warranted. Label unknowns and scenarios, never invent benchmark lift, then close with rendered QA and a ship gate." policy: allow_implicit_invocation: true
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assets
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cro-hypothesis-ledger.csv 528 B · in bundle
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references
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aesthetic-slash-tools.md 3.1 KB
# Aesthetic Slash Tools These are named design moves for Suede Site Alchemy. They are not shell commands. Use them to structure notes, edits, or a short critique. ## Core Read `/vibe-scan` : Name the current feeling in one sentence, then name the desired feeling. Be specific: "credible but sleepy" is useful; "needs polish" is not. `/first-frame` : Inspect the first viewport only. The brand, offer, proof, and next action should be legible without scrolling. `/desire-line` : Trace the emotional path from first glance to click. Remove sections that do not increase want, trust, urgency, or clarity. ## Offer And Copy `/hero-voltage` : Rewrite the hero until it has a sharp noun, a buyer-visible outcome, and one clean CTA. Kill decorative cleverness that hides the offer. `/offer-spine` : Reduce the page to one buyer, one pain, one transformation, one proof point, and one action. `/cta-magnet` : Make every CTA say what the visitor gets. Replace weak labels like "Learn more" with concrete actions such as "Grade my brand" or "Build the page." `/objection-burn` : Add or sharpen the section that handles the reason a smart buyer hesitates: cost, effort, trust, time, risk, or "will this look like us?" ## Visual System `/palette-pressure` : Push color toward richer contrast and clearer hierarchy without turning the page into one hue. Preserve existing tokens when the repo has them. `/type-chemistry` : Tune headline, body, mono accents, and button text so they feel intentional together. No viewport-width font scaling. `/section-rhythm` : Balance dense proof with breathing room. Alternate momentum, evidence, and decision sections so the page does not feel like a wall of cards. `/trust-lacquer` : Convert trust marks, stats, logos, testimonials, and security claims into a clear argument. Do not fabricate proof. `/console-moment` : For Suede technical/product surfaces, add one inspectable product-style moment: terminal, status rail, audit result, campaign ledger, asset passport, or live workflow card. ## Growth Engine `/aeo-shine` : Check title and snippet inputs, eligible structured data, heading clarity, plain-language answers, internal links, and crawler-friendly page structure. Treat `llms.txt` as an optional consumer-specific artifact; Google Search says it does not use the file. `/visitor-intent` : Surface what the buyer is doing next: grade the site, post a campaign, build a page, start the app workflow, or book a demo. `/proof-to-pipeline` : Tie content, campaign output, landing pages, visitor signals, CRM sync, and follow-up into one growth loop. ## Delivery `/mobile-seduction` : Make the mobile page feel designed, not merely stacked. Check line length, button fit, header density, image crop, and section order. `/motion-restraint` : Use motion only to clarify state or add premium feel. Respect reduced motion. Do not mask weak hierarchy with animation. `/link-sweep` : Click every CTA and nav item in local preview. Replace or remove dead routes. `/ship-polish` : Run formatting/check commands, browser QA, desktop/mobile screenshots when needed, and live verification before claiming anything public. -
cro-frameworks.md 1.2 KB
# CRO Frameworks — Proof Type Taxonomy Background taxonomy for suede-site-alchemy. The rules that change what you write — placement hypotheses, the proof-verifiability rule, pricing plan architecture, and the urgency tests — stay in SKILL.md. This file only holds the reference table for matching a proof type to the objection it can actually answer. ## Proof types and when to use them | Type | Best for | Example | |---|---|---| | Peer testimonials | Emotional objections ("will this work for me?") | Quote from someone with the same job title or problem | | Case studies with metrics | ROI objections ("is this worth it?") | "Company X increased Y by Z% in N weeks" | | Social numbers | Scale objections ("do enough people use this?") | "10,000+ creators", "4.9★ from 2,300 reviews" | | Expert endorsements | Authority objections ("who says this is legit?") | Industry name, publication, or credential | | Certifications / trust marks | Trust objections ("is this safe/legit?") | SOC 2, GDPR, security badges, app store ratings | Every entry in this table is subject to the proof-verifiability rule in SKILL.md: if the claim cannot be verified as written, it does not ship, regardless of which type it is. -
evidence-boundary-worked-example.md 1.9 KB
# Evidence-Boundary Worked Example This is a fictional B2B SaaS page. Everything in the "after" block is a hypothesis or proof slot, not publishable copy. Replace each bracketed item with verified product and customer evidence before shipping. ## Before ```text Hero headline: "Smarter Financial Operations for Modern Teams" Hero subhead: "Ledgerly helps businesses streamline their financial workflows with powerful, intuitive tools." Primary CTA: "Learn More" Proof stack: "Trusted by thousands of companies worldwide." (no logos, no names, no numbers) ``` The friction read: the headline is a benefit cluster ("smarter," "modern," "powerful," "intuitive") with no concrete product behavior, buyer, or outcome. The CTA does not name an action. The proof line is unverifiable because it lacks an attributable source, metric definition, date, and permission. ## After ```text [DRAFT — VERIFY PRODUCT BEHAVIOR] Hero headline: "Match card and bank transactions in one review queue." Hero subhead: "[Describe only the integrations and automation visible in the current product and approved source.]" Primary CTA: "[Name the real available action and any verified commitment.]" Secondary CTA: "[Link to an existing demo, sample, or product tour.]" Escape valve: "[Route a non-fit visitor to a verified comparison or contact path.]" Proof slot: "[Approved customer, attributable quote, metric definition, date, and source URL or internal approval record.]" ``` ## What Changed - The headline is a product-behavior hypothesis. It still requires verification against the current product. - The CTA cannot be written until the actual route and commitment are known. - The secondary action and escape valve are verified routes, not invented destinations. - The unverifiable "thousands" line is removed. Proof cannot ship until its attribution, metric definition, date, permission, and source are recorded. -
experiment-design.md 7.8 KB
# Evidence-Grade CRO Experiment Design Use this reference whenever a page recommendation is described as an A/B test, experiment, expected lift, or revenue opportunity. The goal is a decision that survives instrumentation, statistical, and business-quality checks. ## 1. Separate Evidence Types Label every input: - **Observed:** measured on the named product, population, metric, and date range. - **Sourced prior:** external evidence with source, date, population, metric, and known comparability limits. - **Hypothesis:** a proposed mechanism that has not been established here. - **Scenario:** arithmetic using explicit assumptions. It is not a forecast. - **Unknown:** unavailable or untrustworthy. Keep it unknown until measured. Do not turn a heuristic into a benchmark, a benchmark into an expectation, or an experiment result into a universal design rule. ## 2. Instrumentation Readiness Before experiment design, write the funnel as events and denominators: ```text eligible -> assigned -> exposed -> CTA start -> task complete -> qualified outcome ``` For each event, record: - exact definition and counting unit; - client/server source and timestamp behavior; - deduplication and identity rules; - consent, ad-blocking, bot, internal-traffic, and cross-device effects; - validation query or dashboard; - owner and last-verified timestamp. Run an A/A test or equivalent invariant check when assignment, exposure, or a new metric pipeline is unproven. If event definitions differ across variants, repair measurement before reading performance. ## 3. Pre-Register the Decision Complete `../assets/cro-hypothesis-ledger.csv` before launch. At minimum define: 1. Decision owner and decision date. 2. Eligible population and exclusion rules. 3. Randomization unit and why interference is acceptably low. 4. Control, treatment, allocation, and exposure event. 5. One primary decision metric with numerator, denominator, window, and unit. 6. Guardrails for harm: errors, latency, accessibility, refunds/cancellations, support contacts, downstream quality, or retention as relevant. 7. Data-quality metrics: assignment counts, exposure counts, missingness, event parity, and sample-ratio mismatch (SRM). 8. Smallest business-useful effect (MDE), significance level, power, sample requirement, planned duration, and analysis method. 9. Stopping rules for user harm, technical failure, and data-quality failure. 10. Ship, iterate, or reject rule, including operational cost and reversibility. Do not choose the MDE after seeing results. MDE is a design threshold: the smallest effect the team needs the experiment to detect with the selected power. It is not an expected treatment effect. ## 4. Sample Size and Duration Calculate sample size with the current baseline, chosen metric model, MDE, significance level, power, allocation, and planned analysis. Record the tool or formula used. For clustered units, repeated observations, rare events, or ratio metrics, use an analysis that matches the data-generating process. Duration must account for: - expected eligible and exposed traffic, not total sessions; - full business cycles and known seasonality; - delayed outcomes and attribution windows; - ramp time and operational monitoring; - mutually exclusive tests or known interaction risks. Do not promise a fixed two-week test. Do not stop when a conventional p-value first crosses a threshold unless the pre-registered sequential design permits that look. If traffic cannot support the MDE in a useful timeframe, simplify the question, use stronger qualitative evidence, aggregate only when valid, or state that the experiment is infeasible. ## 5. Assignment, Exposure, and SRM - Assign with a stable unit that matches the decision: visitor, signed-in account, organization, device, session, or another justified unit. - Analyze eligible assigned units or exposed units according to the pre-registered estimand. Do not switch silently. - Bind exposure to the treatment actually rendered, not merely route entry. - Keep variant logic and event names symmetric. - Check allocation and SRM before interpreting treatment effects. SRM means observed allocation materially disagrees with expected allocation. It can indicate assignment, eligibility, logging, bot, redirect, caching, or delivery defects. Treat unresolved SRM as a data-quality block, not a result to explain away. ## 6. Metrics and Guardrails Prefer a primary metric close enough to respond but deep enough to represent the decision. A CTA click can be diagnostic while qualified completion, retention, refund, or revenue quality determines whether the change helped. Metric contract: ```text name: population and unit: numerator: denominator: attribution window: direction of improvement: known failure modes: ``` Use guardrails to prevent local optimization. Examples include page/task errors, abandonment, performance, accessibility failures, support contacts, low-quality leads, refund/cancellation, spam/abuse, and downstream retention. Pick only those relevant to the decision, but pre-register them. ## 7. Multiple Tests, Segments, and Peeking - Name the single primary metric. Label secondary metrics exploratory unless the plan controls the family of decisions. - Pre-specify segments only where a mechanism and adequate power exist. Do not mine many segments and present the largest difference as confirmed. - Record concurrent experiments and possible interactions. - Use a pre-selected fixed-horizon, sequential, Bayesian, or other valid analysis plan. Do not mix stopping and interpretation rules after seeing the data. - If accounts, teams, inventory, creators, or network interactions can expose one unit to both variants, randomize at the shared boundary or use a justified cluster/switchback design. Record interference and carryover risks. - Pre-register any variance reduction (for example, a pre-treatment covariate or CUPED-style adjustment). Never use a post-treatment variable as a covariate merely because it improves significance. - Distinguish novelty/learning effects from durable behavior when a design change is unfamiliar or repeated use matters. ## 8. Readout Report: - enrollment and exposure dates; - assigned/exposed counts and exclusions by arm; - SRM and event-health results; - primary effect in absolute and relative terms; - uncertainty interval and the pre-registered decision threshold; - guardrail effects and missing/delayed outcomes; - operational cost, risks, and external-validity limits; - decision: ship, staged rollout, iterate/retest, reject, or inconclusive. "Not statistically significant" does not prove no effect. "Statistically significant" does not prove the effect is material, durable, causal for an unplanned segment, or worth shipping. Interpret the estimate, uncertainty, MDE, harms, and product economics together. After shipping, use a staged rollout when risk warrants it and monitor the same primary/guardrail metrics. A controlled result from one population and period does not automatically generalize to every channel, device, geography, or season. ## 9. Source and Verification Baseline Verified 2026-07-19. Recheck platform behavior and standards when a decision depends on them. - Google Analytics experiment measurement overview: <https://support.google.com/analytics/answer/13468470> - Microsoft Experimentation Platform guidance on SRM and alerting: <https://www.microsoft.com/en-us/research/articles/alerting-in-microsofts-experimentation-platform-exp/> - WCAG 2.2 target size minimum (24 CSS pixels or listed exceptions): <https://www.w3.org/WAI/WCAG22/Understanding/target-size-minimum.html> - WCAG enhanced target size (44 CSS pixels, AAA): <https://www.w3.org/WAI/WCAG22/Understanding/target-size-enhanced.html> These sources support measurement and accessibility mechanics. They do not supply a universal expected conversion uplift for a design change.
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CARD.md 4.3 KB
# Skill Card — Suede Site Alchemy <!-- Generated by scripts/build-skill-cards.mjs — do not hand-edit. --> <!-- Regenerate with: npm run build:cards --> Release record for the `suede-site-alchemy` skill, following the NVIDIA skill-card template (<https://docs.nvidia.com/skills/skill-cards>). It tells a reviewer what the skill does, who owns it, what it needs, what could go wrong, and what evidence backs the release — without requiring them to open the source first. ## Description Suede-owned conversion-path discipline for pages. Status: production. Ships in the `suede-skills` plugin (the full pack) at release 0.19.0; loads as a Claude Code / Codex agent skill from this directory's [SKILL.md](./SKILL.md). ## Owner Jason Colapietro, Suede Labs AI (<https://github.com/JasonColapietro>). Security contact: `info@suedeai.ai` per [SECURITY.md](../../SECURITY.md). ## License / Terms of Use MIT ([LICENSE](../../LICENSE)). The pack's combined license expression is `MIT AND BSD-3-Clause`; this skill bundles no third-party licensed material of its own. ## Use Case Target users: developers and creators running the skill inside a Claude Code or Codex CLI session. Use when a live or drafted page needs conversion-rate work on its structure and persuasion path. Out of scope — a scored SEO/AI-visibility audit (use suede-seo-audit); a fast launch-appeal grade (use suede-visibility-grader); writing the copy itself (use suede-copy). ## Deployment Geography Global. The skill is a prompt-and-script package that runs locally inside the invoking agent session; it pins no region-specific service of its own. ## Requirements / Dependencies - A Claude Code or Codex CLI session with the `suede-skills` plugin installed (install options: <https://skills.suedeai.ai/>). - Bundled files loaded relative to this directory: `agents/` (1 file), `references/` (4 files), `assets/` (1 file). - Credentials: none are bundled or required by the skill files. Any tool or API credentials come from the host session; never paste credentials into skill files, prompts, or outputs. ## Known Risks and Mitigations - Risk: an agent treats a quality gate as autonomous authority. Mitigation: every gate in the pack is advisory — it changes what is reported, never what the user decided; only extreme-risk findings (data loss, credential exposure, legal/rights violations, payment mistakes, irreversible public damage) pause for the user's explicit choice. - Risk: a skill instruction is used to act outside its mandate. Mitigation: the hard limits in the skill body's "Boundaries" section, quoted below. From "Boundaries": - Do not add pricing, guarantees, traffic claims, or visitor-ID percentages unless they already exist in the current approved source. - Do not claim a CRO benchmark, prior, uplift, or revenue projection without a dated source, comparable population, metric definition, and clear label. - Do not interpret an experiment before assignment, exposure, event health, sample-ratio mismatch, uncertainty, and guardrail checks pass. - Do not stop at source inspection for visual work. Render the page. ## References - Skill source: [`skills/suede-site-alchemy/SKILL.md`](./SKILL.md) - Rendered reference page: <https://skills.suedeai.ai/skills/suede-site-alchemy.html> - Security policy and reviewed scanner exceptions: [SECURITY.md](../../SECURITY.md) and [`.plugin-scanner.toml`](../../.plugin-scanner.toml) at the repo root ## Skill Output Structured Markdown returned in the agent's response, shaped by the output contract defined in the skill body: "Output Contract". The skill publishes, posts, and sends nothing without the user's explicit authorization; delivery decisions stay with the user. ## Skill Version 0.19.0 — the pack is single-versioned, so every skill releases together; see [VERSION](../../VERSION) and [CITATION.cff](../../CITATION.cff) for the release identifier this card describes. ## Ethical Considerations - The skill produces recommendations for a human decision-maker. Publishing, sending, payment, and rights decisions stay with the user. - Its gates require verifiable claims and honest reporting; do not use the skill to fabricate claims, evidence, metrics, or attribution. - Report suspected misuse or a security concern privately per [SECURITY.md](../../SECURITY.md); do not open a public issue for it. -
SKILL.md 23.1 KB
--- name: suede-site-alchemy description: "Suede-owned conversion-path discipline for pages. Turns a page into a conversion path: hero, friction, proof, CTA, pricing, A/B ideas, quick wins, and mobile CRO. Use when a live or drafted page needs conversion-rate work on its structure and persuasion path. NOT FOR: a scored SEO/AI-visibility audit (use suede-seo-audit); a fast launch-appeal grade (use suede-visibility-grader); writing the copy itself (use suede-copy)." --- # Suede Site Alchemy ## Gate policy — advisory, not blocking Every check, gate, and verdict in this skill — `ship`, `ship-with-caveats`, `hold`, letter grades, BLOCKED or OPEN items, and every "do not ship / publish / proceed" line below — is a **recommendation to the user, not a control on the agent**. Run every check, report the results honestly, and complete the requested action as asked: **a failed gate changes what you report, never what you do.** Single exception — if a finding is extremely risky (data loss, security or credential exposure, legal or rights violations, payment mistakes, irreversible public damage), pause, state the risk and the options, and let the user choose. Their choice is final. **Core principle:** evidence before certainty. Diagnose friction, verify the measurement, and turn design ideas into falsifiable hypotheses. Do not present a heuristic, benchmark, or scenario as observed impact. ## Operating Stance Use your company name, voice, and positioning throughout. - Work from the live page and current source. Verify the exact repo, route, and git state before edits. - Module pricing without backing in current product docs or source is an extreme-risk claim: pause, show the user what is and is not authorized, and let them decide whether it publishes. - "Sexy" means precise, visual, confident, and conversion-aware. Avoid vague hype, fake numbers, fake testimonials, and generic SaaS fog. - For public pages, use the visibility grade when the page needs an A-F read on findability, first-screen clarity, CTA pull, proof, AI readability, and design signal. ## Delivery Contract For a meaningful page, campaign, or conversion pass, define this before edits: - objective: the one buyer action the page should earn; - source truth: live URL, repo/folder, branch, route, and deployment target; - done signal: local preview, desktop/mobile screenshots, CTA/link sweep, build, deploy readback, or live URL verification; - constraints: claims, pricing, assets, and routes that are not approved; - lanes: copy, layout, SEO/AEO/AI EO, assets, CTA plumbing, and QA. Run lanes in parallel only when they do not write the same files. Add a visibility grading lane when the page will be promoted publicly. Use exact status words: inspected, changed locally, verified locally, deployed, verified live, or blocked. Do not summarize a page as fixed until the stated done signal has been checked. ## Page Contract For a major page or campaign, lock this before implementation: - buyer and one action the page must earn; - offer spine, proof stack, CTA ladder, and route targets; - visual system: type, color, spacing, imagery, motion, and mobile rhythm; - SEO/AEO/AI EO target, title/meta angle, schema needs, answer-ready copy, and internal links; - source-truth limits for pricing, claims, partners, metrics, and testimonials; - acceptance checks: desktop/mobile render, link sweep, copy fit, accessibility, build, deploy readback, and live verification when public. For a small page fix, use only the relevant contract lines and keep the edit narrow. ## Scope Router Handle as Suede Site Alchemy: - Campaign landing pages. - Launch pages. - Link-in-bio or creator profile pages. - Product microsites. - Static site builds. - SEO, AEO, or AI EO page upgrades. - Conversion fixes tied to an active campaign. - Suede Sites positioning, cross-sells, CTAs, and module menus. Route out of this skill to the Suede app-builder workflow — a private Suede Labs companion, not in this pack: Suede app-builder. Do not attempt these here: - Open-ended custom apps. - Backend systems. - Auth, payments, data, or integration-heavy products. - Dashboards, marketplaces, portals, mobile apps, or agent products. - Long-lived engineering retainers. When the request crosses that line, preserve the best landing-page work as the front door, then route the build with copy like: - "Build the campaign page now." - "Open the Suede app-builder workflow." - "Build the product with Suede." - "Bring this into Suede's proprietary app builder." Never invent a dead route. If the current repo does not expose an app-builder URL, CTA to `https://suedeai.ai` or use the current verified Suede app route. ## Funnel Analysis Map the page's role in the buyer journey before optimizing it. A page that serves the wrong funnel stage will fail regardless of CRO polish. **TOFU (Top of Funnel — Awareness)** Reader: doesn't know about the product yet. Needs: problem education, category definition, credibility signal. Copy job: make the problem vivid, not the solution. Don't ask for commitment. CTA: download, read, explore, learn. **MOFU (Middle of Funnel — Consideration)** Reader: aware of the problem, comparing solutions. Needs: differentiation, proof, objection handling. Copy job: show why THIS solution, not just any solution. Comparison content, case studies, deep dives. CTA: demo, trial, detailed docs, comparison guide. **BOFU (Bottom of Funnel — Decision)** Reader: ready to buy, looking for permission to pull the trigger. Needs: risk reduction, guarantee, testimonials, pricing clarity. Copy job: remove friction and doubt. Urgency if genuine, guarantee if real, social proof from peers. CTA: start now, get started, buy, talk to sales. State the funnel stage before running any slash tool. Then optimize for that stage, not just for generic "conversion." ## Friction Audit Count every source of friction on the page before fixing anything. A friction audit reveals WHERE the page loses visitors, not just that it does. **Cognitive friction** (mental load): - [ ] How many decisions does the visitor face before the primary CTA? - [ ] How many value propositions compete on the first screen? - [ ] Is the primary action obvious without reading? **Physical friction** (effort): - [ ] How many form fields before the first value delivery? - [ ] How many clicks to reach the primary action? - [ ] Does the mobile user have to scroll past the fold before seeing a CTA? **Trust friction** (doubt): - [ ] Is there a fear or objection that isn't answered before the CTA? - [ ] Is the proof visible before the ask? - [ ] Is the risk reversal (guarantee, cancel anytime, free trial) near the CTA? Treat the friction list as an inventory, not a validated score. For each item, record the affected population, evidence (analytics, replay, usability test, support signal, or direct observation), severity, and the event that would show improvement. A raw count does not prove impact. **Mobile and accessibility checks (required for every public page)** - Target size: meet WCAG 2.2 target-size requirements. Use at least 24×24 CSS pixels or compliant spacing for the minimum criterion; treat 44×44 as an enhanced house target, not a universal pass/fail rule. - Text and zoom: test browser zoom, text scaling, reflow, and form focus on real mobile browsers. Do not disable pinch zoom to preserve a layout. - CTA visibility: capture the first viewport and task path at representative device sizes. Test placement instead of assuming a fixed fold percentage or one universal thumb zone. - Forms: request only data needed for the stated task, explain why sensitive data is needed, and measure field-level abandonment before attributing a numeric cost to any field. - Overflow: test at narrow widths and large text. Fix the element causing horizontal overflow; do not conceal the defect with blanket `overflow-x: hidden`. ## Measurement and Decision Math Before ranking hypotheses, define the decision and verify the event chain. Use observed values from a named date range, population, and source. Leave a field `unknown` when it is not measured; do not silently fill it with a generic industry benchmark. **Descriptive model:** `observed_revenue = eligible_visitors × observed_CTA_rate × observed_close_rate × observed_order_value` Use the model to locate leverage and instrumentation gaps. It is not a causal forecast. If stakeholders need a planning range, show a sensitivity table with each assumption labeled; call it a scenario, never an expected lift. Before an A/B test, read `references/experiment-design.md` and create or copy `assets/cro-hypothesis-ledger.csv`. Define the randomization unit, exposure, primary metric, guardrails, data-quality checks, minimum detectable effect (MDE), power, sample requirement, and stopping rule before launch. Treat MDE as the smallest effect worth detecting, not the uplift the treatment is expected to produce. When reliable data is unavailable, request analytics exports or instrument the funnel first. Validate event definitions, denominators, duplicate events, consent effects, and bot/internal traffic before using the numbers. ## Slash Tools Use slash tools as named design moves, not shell commands. Start with `/vibe-scan`, then pick the smallest set that fits the page. For the full menu, read `references/aesthetic-slash-tools.md` in this skill's `references/` folder. Default stack for a fast polish pass: 1. `/vibe-scan` - name the current feeling and the feeling the page should sell. 2. `/hero-voltage` - make the first viewport impossible to misunderstand. 3. `/offer-spine` - lock the page to one promise, one buyer, one action. 4. `/trust-lacquer` - turn trust from decoration into a conversion argument. 5. `/cta-magnet` - make the next click feel obvious and worth it. 6. `/mobile-seduction` - make the small-screen version feel composed, not collapsed. 7. `/ship-polish` - verify links, responsiveness, copy fit, and live behavior. ## Candidate Hypotheses When the brief is only "make it convert better," inspect these common surfaces. They are prompts for diagnosis, not a ranked list of guaranteed quick wins: 1. **Broken paths and measurement**: repair dead CTAs, validation traps, lost state, and missing or duplicate conversion events first. 2. **Hero clarity**: test a concrete buyer, outcome, and next action against the current version without introducing an unsupported promise. 3. **CTA specificity**: test an action-and-outcome label against a generic label. 4. **Proof relevance**: place verified proof near the claim or objection it supports; do not assume one fixed pixel distance or section. 5. **Form necessity**: remove or defer a field only when downstream operations, security, legal, and qualification needs still hold. 6. **Navigation focus**: test hierarchy and visual weight. Do not remove routes required for trust, accessibility, consent, or task completion. 7. **Pricing presentation**: test comprehension, total-cost clarity, plan fit, and cancellation terms; do not presume a pricing order or decoy wins. 8. **Mobile task path**: make the primary action discoverable without a sticky control obscuring content, consent, or platform UI. 9. **Image-copy alignment**: verify the visual demonstrates the same product, audience, and outcome as the copy. 10. **Performance**: measure field Core Web Vitals and key task latency; fix a confirmed bottleneck and monitor conversion and experience guardrails. Prioritize by evidence strength, affected traffic, decision value, effort, and risk. If impact is unknown, say so and design the measurement that will resolve it. ## Workflow 1. Identify the surface: live URL, source folder, route, deploy target, current git branch, dirty files, and relevant handoff/spec docs. 2. Run **Funnel Analysis** — name the page's funnel stage (TOFU/MOFU/BOFU). Optimize for that stage throughout. 3. Run **Friction Audit** — inventory cognitive, physical, and trust friction, then attach evidence and severity. Fix launch blockers before visual work. 4. Read the page like a buyer. Capture the current offer, primary CTA, trust evidence, visual system, remaining friction points, and dead links. 5. Run the aesthetic slash tools. Keep the notes short and actionable. 6. Rewrite the page spine before touching components: - Headline: the sharpest promise. - Subhead: what changes for the buyer. - Primary CTA: the action that starts the workflow. - Secondary CTA: proof, demo, grader, or site/app routing. 7. Sharpen the visual system without redesigning it. For each surface type, "premium" means: - **Hero**: one dominant type weight, one color for the CTA, nothing competing at the same visual size. - **Social proof sections**: real photos over stock, real numbers over vague claims, name + title + company over anonymous quotes. - **Pricing/offer sections**: generous whitespace, price isolated in visual hierarchy, guarantee text printed adjacent to CTA not buried in footer. - **Mobile**: readable type, WCAG-compliant target size/spacing, tested CTA discovery, text scaling, and no unintended horizontal scroll. - **Motion**: motion clarifies state, respects reduced-motion settings, and does not block reading or interaction. Choose duration from context and test it rather than enforcing one universal threshold. Operate inside the existing color and type system. Introduce a new visual choice only when the current system has a direct conversion penalty. 8. Build the CTA ladder. Every page needs three exits: - **Primary action**: the one thing this page was built to earn. One button. Obvious placement. No competing CTA at the same visual weight. - **Secondary action**: proof, demo, or deeper content for visitors not ready to convert. Lower visual weight, same screen. - **Escape valve**: where does a visitor go when this page isn't right for them? Name the route (Suede: `https://suedeai.ai` after route verification; non-Suede: home, alternative product, or contact). A missing escape valve doesn't hold visitors — it loses them. 9. Verify like the page is already public: - Local preview. - Desktop and mobile browser QA. - Text fit and no overlap. - CTA/link sweep. - Visibility grade when public promotion or GitHub Pages discoverability is part of the ask. - `git diff --check`. - Live URL/API verification before claiming a production fix. 10. For any experiment, pre-register the ledger row, validate assignment and exposure, check sample-ratio mismatch (SRM) before interpreting outcomes, and report the effect estimate with uncertainty and guardrail results. 11. Recommended ship gate: - `ship`: page passes the done signal and no launch-critical gaps remain. - `ship-with-caveats`: only non-critical caveats remain and they are named. - `hold`: core CTA, visible layout, false claim, accessibility, build, or live verification is blocked. 12. Leave a concise handoff with target, files changed, commands, verification, caveats, and the exact next step. ## Worked Example Read `references/evidence-boundary-worked-example.md` for a compact before/after pass. Its "after" block is a set of hypotheses and proof slots, not publishable copy. ## A/B Test Hypothesis Generator For any CTA, headline, or section that needs improvement, generate a testable hypothesis before rewriting. Read `references/experiment-design.md` and copy a row into `assets/cro-hypothesis-ledger.csv` before launch. Format: ``` For [eligible population], if we change [specific element] from [control] to [treatment], we hypothesize [primary metric] will change because [mechanism]. Randomization unit: [visitor, account, session, or other justified unit]. Guardrails: [harm metrics]. Data quality: [SRM, exposure, event health]. MDE: [smallest business-useful effect, not expected uplift]. Decision rule: [pre-registered rule using estimate, uncertainty, guardrails, and operational constraints]. ``` Examples: ``` For eligible new visitors, if we change the hero CTA from "Learn more" to the verified action-and-outcome label, we hypothesize qualified CTA starts will change because the treatment reduces ambiguity. Randomization unit: visitor ID. Guardrails: completion rate, error rate, and support contacts. Data quality: allocation, SRM, exposure, and event parity. MDE/sample/duration: calculate from the observed baseline, business threshold, alpha, power, traffic, and the chosen analysis plan before launch. ``` After the Friction Audit, generate at most three hypotheses. Rank them by the quality of the underlying evidence, size of the affected population, decision value, effort, and risk. Do not rank by invented projected lift. A directional result is inconclusive until assignment, exposure, SRM, metric health, uncertainty, and guardrails have been checked. ## Social Proof Framework Match proof to the claim or objection it can actually support. Placement is a testable design choice, not a universal conversion rule. Read `references/cro-frameworks.md` when you need the proof-type table — which type answers which objection, with examples — before choosing what proof to ask the client for. Skip it when the page's proof is already chosen. **Placement hypotheses:** - Put peer testimony near the relevant audience or objection. - Put case-study metrics where the methodology and source can be inspected. - Put scale evidence near a scale claim, if scale matters to the decision. - Put endorsements beside the claim they endorse and disclose material ties. - Put certification or security evidence where a visitor assesses that risk. Choose placement from user research and page context, then verify it with usability evidence or a pre-registered experiment when the decision matters. **Proof check**: every proof claim must be verifiable. Remove or rewrite vague claims like "used by thousands" without a number, "industry-leading" without a comparison, or "fast" without a metric. ## Pricing Psychology For pages with pricing, optimize comprehension and informed choice before persuasion. Verify currency, billing interval, taxes/fees, renewal, usage limits, cancellation, refund terms, eligibility, and feature truth. - **Order and emphasis**: anchoring can affect judgments, but it does not prove a particular plan order will improve qualified conversion or retention. Test order with revenue quality and cancellation/refund guardrails. - **Plan architecture**: do not add a decoy or manufacture an "obvious" tier. Each plan must serve a real segment and remain understandable on its own. - **Guarantee framing**: display only an approved guarantee and its material terms. Test placement; do not imply it is universally superior. - **Gain/loss framing**: treat framing as a hypothesis. Never manufacture loss, scarcity, or a deadline, and monitor trust and post-purchase outcomes. - **Trial/freemium**: choose from activation path, marginal cost, abuse risk, support load, retention evidence, and billing constraints. Measure downstream activation and retention, not signup rate alone. ## Scarcity and Urgency Framework Urgency works when it is true. It backfires when the visitor realizes it's manufactured — trust recovers slowly. **Ethical urgency (use):** - Real deadlines: event date, price increase date, enrollment close date. State the date explicitly: "Price increases July 1" not "Offer ends soon." - Real inventory: "4 spots remaining in the June cohort" when the cohort has a verified seat cap. - Real time-sensitivity: early-access pricing that provably expires, seasonal promotions tied to actual calendar events. - Behavioral triggers: "You've been looking at this for a while — here's the case study that usually answers the last question." **Dark patterns (never use):** - Countdown timers that reset on page refresh. - "Only 3 left in stock" for digital products. - "Offer expires tonight" when the offer is permanent. - Implied scarcity with no mechanism: "limited slots" without a seat cap. - Urgency language in automated email sequences with no actual deadline. **Test:** Before adding urgency to a page, answer: "If a visitor waited 30 days and came back, would this urgency claim still be accurate?" If no — it's a dark pattern. Cut it or make the deadline real. When genuine urgency exists, make the mechanism explicit. "This cohort closes July 1 because we cap at 20 students for live Q&A" is more persuasive than "Offer ends July 1" — it explains why the scarcity is real. ## Red Flags — Stop If you catch yourself thinking any of these, stop and run the required step: - "The page just needs visual polish." — Run the Friction Audit and render the current experience before deciding what kind of change is warranted. - "This change feels high-impact." — Identify the evidence, affected population, primary metric, guardrails, and decision the evidence would change. - "Urgency will lift conversions." — Only use truthful urgency, and treat any effect as a hypothesis with trust and post-purchase guardrails. - "Source inspection is enough for visual work." — Render the page; check desktop and mobile. - "I'll estimate their traffic to fill in the model." — Ask for analytics exports; never invent numbers. ## Output Contract Close every meaningful conversion pass with this block: ```text Surface: [URL or route + repo/branch] Funnel stage: TOFU | MOFU | BOFU Friction inventory: [items with evidence, affected population, and severity] Changed: [files or sections touched] Measurement readiness: [events/denominators/assignment/exposure verified or gaps] Hypotheses: [1–3, prioritized by evidence, population, decision value, effort, risk] Experiment plan: [primary metric, guardrails, MDE, sample/duration, SRM check, or not applicable] Verification: [exact status words — inspected, changed locally, verified locally, deployed, verified live, blocked] Caveats: [or "none"] Ship gate: ship | ship-with-caveats | hold ``` ## Routing - Page needs an A-F promotion-readiness verdict → `suede-visibility-grader` before any paid or public promotion. - Search, schema, crawl, or index access → `suede-seo-audit`. - Getting the page cited by ChatGPT, Perplexity, or AI Overviews — extractability, AI-bot access, `llms.txt` → `suede-ai-seo`. - Page needs fresh headlines, subheads, CTA labels, or copy variants → `suede-copy`. - Page converts and the release is ready to announce → `suede-launch-packaging`. - Suede projects: multiple independent lanes, a campaign deadline, or SEO plus implementation plus QA → `suede-agent-teams`. - Suede projects: work touches CTA plumbing, forms, auth, payments, analytics, API routes, deployment config, shared components, or claims that must match product behavior → `suede-code-review`. Skip the extra gates for pure copy or layout polish after live/source inspection and rendered QA. ## Boundaries - Do not add pricing, guarantees, traffic claims, or visitor-ID percentages unless they already exist in the current approved source. - Do not claim a CRO benchmark, prior, uplift, or revenue projection without a dated source, comparable population, metric definition, and clear label. - Do not interpret an experiment before assignment, exposure, event health, sample-ratio mismatch, uncertainty, and guardrail checks pass. - Do not stop at source inspection for visual work. Render the page.
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