LLM Mart Basic
@llm-mart · Joined Jun 2026
Full SEO audit: Google Search Console data + URL Inspection API + PageSpeed Insights API + technical crawl + keyword research + metadata audit + schema markup audit + search intent analysis + Core Web Vitals monitoring. Feeds real GSC data and PageSpeed metrics into AI to surface
SEO drift monitoring — snapshot a site's SEO state and detect regressions over time. Captures a baseline (rankings/positions, indexed page count, titles & meta descriptions, canonical/robots directives, schema presence, key on-page elements) and on later runs diffs against it to
Single-page SEO audit: deep content quality evaluation using Google's E-E-A-T framework, Helpful Content guidelines, on-page SEO factors, search intent alignment, technical signals, and readability analysis. Fetches GSC performance data for that specific page, crawls the live HTM
Connect a CMS to notfair SEO tools. Guides users through configuring WordPress, Strapi, Contentful, or Ghost — tests the connection, and writes credentials to .env.local. Once set up, seo-analysis automatically cross- references CMS content against Google Search Console data. Use
XML sitemap audit — find and fix the sitemap problems that quietly waste crawl budget and slow indexing. Discovers the sitemap (robots.txt, /sitemap.xml, sitemap index), validates structure and size limits, and cross-checks the URLs it lists against reality: non-200 / redirected
Search Experience Optimization (SXO) — the bridge between SEO and UX/CRO. Audits the full journey from the SERP click to the on-page goal: SERP click-through factors (title/meta/rich results that win the click), then post-click experience signals that keep users and drive convers
Upgrade the NotFair plugin to the latest version. Updates the marketplace repo, installs the new version to the plugin cache, and updates installed_plugins.json. Use when asked to "upgrade notfair", "update notfair", or "get latest version". Also handles inline upgrade prompts wh
Use when writing or modifying code in a project that uses BlockWatch — proactively link co-dependent code with `<block affects=...>`/`<block name=...>` so it catches drift when one side changes without the other (an enum and its docs, a constant and its config), or assert two pla
Web accessibility patterns for news and academic sites. Use for WCAG audits, alt text, accessible data viz, and assistive tech.
Scans the session for lessons and workflows, then proposes scoped CLAUDE.md edits. Use for save this lesson or add to context.
Manages attention and evidence in long agent sessions. Use for lost instructions, dropped evidence, or large multi-agent contexts.
Directs the current request through configured lower-tier agents. Use only for explicit /director or /dev-toolkit:director invocation.
Remote JavaScript console and debugging on mobile. Use for phone/tablet console errors, responsive testing, Eruda, and vConsole.
Flags irreversible decisions before commit. Use for data models, infra, auth boundaries, API contracts, event schemas, CI/CD.
Python data pipelines with modular architecture. Use for content workflows, batch jobs, or Google Sheets/Drive integration.
Enforces a test-driven bug-fixing workflow. Use when a user reports a bug, failing code, an error, or asks to fix something.
AI-assisted coding with Claude Code, Cursor, Copilot, Codex, Aider, or Windsurf. Use to build or debug generated code.
Authorized web scraping with fallback cascades and access-failure handling. Use for social media, yt-dlp, CAPTCHA or 403 blocks.
Signs of taste in web UI. Use when building or reviewing web interfaces, dashboards, SaaS apps, or internal tools.
Zero-build frontend development for static apps, browser extensions, maps, and lightweight data-backed interfaces. Use when deployment must not require a build step.
Use MCP Inspector to connect to local or remote servers, inspect capabilities, call tools, read resources, test prompts, and diagnose failures before release.
Build an MCP server in TypeScript with focused tools, validated schemas, local and remote transports, Inspector tests, and production security controls.
An MCP server exposes tools, resources, or prompts through a standard protocol so an AI application can discover and use external capabilities.
Treat an AI agent skill as both an instruction package and a software dependency: inspect what it says, what it runs, what it can access, and how it updates.
Add remote HTTP or local stdio MCP servers to Claude Code, choose the right scope, protect credentials, verify the connection, and test with least privilege.
Skills teach Claude a repeatable method, connectors provide governed access to apps and live data, and plugins package related capabilities for installation and sharing.
Use an agent skill to package reusable know-how and workflow instructions. Use an MCP server when an agent needs live, governed access to external data or actions.
Custom commands and skills can both create a slash-invoked workflow in Claude Code. The important choice is how the workflow is discovered, shared, and permissioned.
A useful Claude skill solves one recurring engineering job, is easy to inspect, and saves more time than it creates in setup and review.
Claude skills can live in your Claude account, your local Claude Code setup, or a repository. Install them where the sessions that need them can load them.
Build a portable AI agent skill from one repeatable job: a precise description, concise instructions, focused resources, and tests that prove it works.
AI agent skills package instructions, scripts, references, and templates into portable folders an agent loads only when the task calls for them.
AI made publishing cheap, which is exactly the problem. What separates a page worth ranking from a competent summary of the first ten results.
A prompt that works once isn't a quality system. Five cases, an observable rubric, and a regression set will tell you whether a change helped.
One character of YAML, four pods that never started, and two safety nets I didn't know were holding. Every restart is an audit. Schedule them before they schedule you.
"Verify your work" isn't an instruction. It's a mood. Here's the version that's an instruction. Verify with a different mechanism than the one that made the claim.
A prompt that works once may still fail in production. A lightweight eval set gives you repeatable cases, a clear rubric, and a way to see whether a prompt change actually improved the workflow.
The best AI tool is not the one with the longest feature list. It is the one that solves a defined job reliably, fits the workflow, handles data appropriately, and remains useful after the novelty wears off.
Use AI to speed research without losing trust. Learn to find primary sources, verify claims, preserve uncertainty, and keep an auditable source trail.
Better prompts aren't magic wording. They're short briefs that hand the model a task, the context it can't infer, the limits, and a quality bar.
/deps-audit
Deps audit
Audit project dependencies for vulnerabilities, outdated packages, license conflicts, and supply chain risks — then provide actionable remediation strategies.
/refactor-clean
Refactor clean
Refactor provided code for cleanliness, maintainability, and alignment with SOLID principles and modern best practices — no over-engineering.
/tech-debt
Tech debt
Analyze and remediate technical debt — inventory debt items, score by impact, and produce a prioritized remediation plan with estimated effort.
/full-review
Full review
Orchestrate comprehensive multi-dimensional code review using specialized review agents across architecture, security, performance, testing, and best practices
/pr-enhance
Pr enhance
Enhance a pull request with a generated description, review checklist, risk assessment, and test coverage report
/implement
Implement
Execute tasks from a track's implementation plan following TDD workflow
/manage
Manage
Manage track lifecycle: archive, restore, delete, rename, and cleanup
/new-track
New track
Create a new track with specification and phased implementation plan
/revert
Revert
Git-aware undo by logical work unit (track, phase, or task)
/setup
Setup
Initialize project with Conductor artifacts (product definition, tech stack, workflow, style guides)
/status
Status
Display project status, active tracks, and next actions
/context-restore
Context restore
Restore saved project context and decisions to resume a session
/context-save
Context save
Save project context, decisions, and progress for a later session
/data-driven-feature
Data driven feature
Build features guided by data insights, A/B testing, and continuous measurement
/data-pipeline
Data pipeline
Design and implement batch and streaming data pipelines with ingestion, orchestration, dbt transformations, data quality checks, and monitoring
/cost-optimize
Cost optimize
Reduce cloud costs across AWS, Azure, and GCP through rightsizing, reserved and spot capacity, storage tuning, and cost monitoring
/migration-observability
Migration observability
Migration monitoring, CDC, and observability infrastructure
/sql-migrations
Sql migrations
SQL database migrations with zero-downtime strategies for PostgreSQL, MySQL, SQL Server
/smart-debug
Smart debug
AI-assisted smart debugging — parse error messages, stack traces, and failure patterns to identify root causes and produce a fix with automated observability steps.
/deps-audit
Deps audit
Audit project dependencies for vulnerabilities, outdated packages, license conflicts, and supply chain risks — then provide actionable remediation strategies.
Make any song you can imagine
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