LLM Mart Basic
@llm-mart · Joined Jun 2026
Analyzes frequency data across your Meta campaigns, identifies where you're overserving ads to the same people, and recommends frequency caps by campaign objective. Tells you the point where additional impressions stop driving conversions and start burning money. Platform: Meta.
Breaks down campaign performance by geographic location at whatever level matters — country, state, city, DMA, zip code. Flags underperforming geos that are quietly eating budget and high-performing ones that deserve more spend. Recommends geo bid adjustments or campaign splits.
Comprehensive Google Ads account health analysis detecting wasted spend, search term leaks, negative keyword gaps, bid strategy issues, and Quality Score problems. Use when analyzing campaign data, pasting Google Ads exports, reviewing account performance, or requesting a full di
Build detailed B2B buyer personas with pain points, objections, buying triggers, and messaging angles. Use when given a product and market to research ideal customer profiles, creating buyer personas, or needing to understand who you're selling to before launching campaigns. Plat
Identifies where your own keywords and campaigns are competing against each other in Google Ads auctions. Finds duplicate keywords across campaigns, overlapping match types that trigger the same queries, and ad groups stealing traffic from each other — all of which inflate your C
Reviews your landing pages against the ads driving traffic to them. Checks for message match between ad copy and page content, CTA clarity, above-the-fold alignment, form friction, and flags any disconnects between what the ad promises and what the page delivers. Platform: Google
CRO analysis for landing pages evaluating headline clarity, CTA placement, trust signals, mobile friction, and conversion killers. Use when uploading a landing page screenshot, pasting a URL for review, requesting conversion rate optimization feedback, or auditing page effectiven
LinkedIn Ads campaign analysis for B2B marketers detecting CTR issues, audience quality problems, lead gen form friction, and budget inefficiencies. Use when pasting LinkedIn campaign exports, analyzing B2B ad performance, or auditing LinkedIn advertising spend. Platform: LinkedI
Meta/Facebook/Instagram Ads campaign structure analysis detecting creative fatigue, audience overlap, scaling opportunities, and iOS tracking verification issues. Use when pasting Meta account data, analyzing Facebook ad performance, reviewing Instagram campaigns, or requesting a
Tracks daily spend against monthly budget targets across all campaigns and accounts. Tells you exactly where you'll land at current pace, flags campaigns that are over or underspending, and calculates the daily budget adjustments needed to hit your target by month end. Platform:
Compares your key metrics against industry benchmarks for your specific vertical, campaign type, and platform. Tells you where you're ahead, where you're behind, and where there's room to improve — adjusted for your account size and spend level, because a $10K/month account and a
Create scalable programmatic SEO page templates with title patterns, internal linking logic, schema markup, and thin content avoidance strategies. Use when given a niche and data source to build page templates, establishing programmatic SEO structure, or scaling content productio
Breaks down Quality Score components for your Google Ads keywords — expected CTR, ad relevance, and landing page experience — and tells you exactly which component is dragging each keyword down, with specific fixes ranked by potential CPC impact. Platform: Google.
Reddit Ads campaign analysis detecting community targeting issues, creative fatigue, bid inefficiencies, and subreddit performance problems. Use when pasting Reddit Ads data, analyzing subreddit targeting, or auditing Reddit advertising spend for B2B or B2C campaigns. Platform: R
Analyzes your conversion lag data to determine the optimal retargeting window for each audience segment. Tells you whether your 30-day retargeting window should actually be 7 days, 14 days, or 60 days based on when people actually convert after their first visit. Platform: Meta.
Projects your ROAS for the next 30, 60, and 90 days based on current performance trends, seasonality patterns from your historical data, and planned budget or campaign changes. Gives you a range with confidence intervals, not a single number pretending to be precise. Platform: Go
Analyzes your search term reports across all campaigns and surfaces high-intent terms you're not bidding on yet. Groups them by theme, estimates their potential volume and CPA, and recommends match types and starting bids for each. Platform: Google.
Generate consistent UTM parameters, GA4 event naming, and conversion tracking specs following taxonomy best practices. Use when describing campaign structure, requesting UTM links, needing GA4 event names, or wanting to standardize tracking nomenclature across marketing channels.
Scans your Google and Meta accounts for money being spent on search terms, placements, audiences, and ads that produce zero or near-zero conversions. Delivers clean exclusion lists you can upload directly. Platform: Google and Meta.
Generates a plain English summary of everything that happened across all your accounts this week. What improved, what declined, what needs immediate attention, and what to prioritize next week. The Monday morning briefing that saves you an hour of pulling reports and context-swit
Fourteen posts of being wrong in production, compressed to checkboxes
Healthy nodes, a quiet network, 300 restarts in three days, and a latency budget measured in milliseconds
Discovery worked. Ping worked. Every TCP connection timed out, and later the tunnel only worked when someone had a terminal open.
Every VM came back. The cluster did not. Declarative systems converge on config, and the datapath isn't config.
A surprising share of AI-in-the-terminal failures aren't the AI. They're zsh, and a version of bash from 2006.
A Claude Code plugin turns standalone project configuration into a namespaced, installable extension that teams and communities can update as one unit.
None of the safety came from the model. It came from six boring habits.
Skills package instructions and references. Subagents run work in a separate context and return results. They solve different problems and can be composed deliberately.
Six hours in, one step left, everything green, and the incident that didn't happen
CLAUDE.md carries persistent project context. Skills load reusable procedures when relevant. Separating stable facts from task-specific workflows keeps both easier to maintain.
Twenty minutes recovering secrets that never existed, and the one sentence from a human that ended it
An API request routing a model's tool call through an approval gate to a remote MCP server
31 config keys, two audits, and why the first one was wrong in both directions
The official MCP Registry stores standardized server metadata rather than package code. Publishers verify a namespace, describe installation or remote access, and submit immutable versions.
Everyone looks at the Dockerfile. The file that actually leaked the key was the project file.
Remote MCP authorization uses established OAuth standards, but secure integration still requires issuer validation, least-privilege scopes, protected token handling, and server-side enforcement.
"Copy it over and switch the reference" is two steps, and the outage lives in the one nobody checks
stdio fits local processes and prototypes. Streamable HTTP fits hosted services and shared integrations. The right choice follows where the capability runs and who must reach it.
The most important rule wasn't about what I could change. It was about what I was allowed to display.
Tools perform operations, resources expose readable context, and prompts provide reusable templates. Choosing the correct primitive makes an MCP server easier to understand and govern.
/standup
Standup
Daily standup: all 9 departments report on the current project in parallel
/analyze-misfires
analyze-misfires
Identify skills injected where not needed, propose regex and description tightening
/announce
announce
Draft X/Twitter announcement post (or thread) for the latest plugin release
/audit-plugin
audit-plugin
Deep quality audit of all skills, agents, and commands for inconsistencies, gaps, duplication, and token waste
/diagnose-negatives
diagnose-negatives
Analyze negative-signal sessions for a skill, identify failure patterns, propose and apply fixes
/eval-skills
eval-skills
Eval all skills with sufficient data, rank by procedure-following score, identify candidates for optimization
/evolve-skill
evolve-skill
Propose a skill revision and compare fresh executions under a frozen rubric
/prune-sync-log
prune-sync-log
Prune stale entries from the whetstone sync decision log
/release
release
Bump version, commit, push, mirror to ai-skills, and update local plugin
/skillopt
skillopt
Run the SkillOpt process-skill optimizer (offline, local). Default prints the exact bare-terminal command (safe); --run executes it in-session (hardened + checkpointed).
/sync-from-repos
sync-from-repos
Analyze reference repos and recommend skill/agent/command improvements based on cross-repo patterns
/triage-prs
triage-prs
Triage all open PRs with parallel agents, label, group, and review one-by-one
/write-skill
write-skill
Author a new skill from scratch with paired trigger fixtures and full validation. Use when adding a skill that has no upstream skills.sh source (discipline, meta, or internal-pattern skills).
/ia-adr
ia-adr
Create Architecture Decision Records with format selection and lifecycle management
/ia-agent-native-audit
ia-agent-native-audit
Score each of the 5 agent-native principles (parity, granularity, composability, emergent capability, improvement-over-time) against a codebase and report gaps
/ia-brainstorm
ia-brainstorm
Explore requirements and approaches through collaborative dialogue before planning implementation
/ia-changelog
ia-changelog
Create engaging changelogs for recent merges to main branch
/ia-deepen-plan
ia-deepen-plan
Expand each section of a plan via parallel research agents that add framework specifics, library conventions, and concrete implementation steps
/ia-document-release
ia-document-release
Post-ship documentation sync. Reads all project docs, cross-references the diff, updates README/ARCHITECTURE/CONTRIBUTING/CLAUDE.md to match what shipped, polishes CHANGELOG voice, and optionally bumps the version.
/ia-feature-video
ia-feature-video
Record a video walkthrough of a feature and add it to the PR description
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