Claude Skills
The open format is called Agent Skills and works in Claude Code, Codex, Cursor and other agents — most people know it as Claude Skills.
Every Agent Skill we could find on GitHub, deduplicated by content. 86 696 files from 2 113 authors, of which 68 413 are unique — the rest is the same skill repackaged into someone else's repository. For each one: what it weighs in tokens, whether it ships runnable scripts, and which MCP servers it needs.
Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.). This skill should be used when conducting systematic literature reviews, meta-analyses, research synthesis, or comprehensive literature searches across biomedical, scientific, and technical domains. Creates professionally formatted markdown documents and PDFs with verified citations in multiple citation styles (APA, Nature, Vancouver, etc.).
This skill should be used when converting academic papers into promotional and presentation formats including interactive websites (Paper2Web), presentation videos (Paper2Video), and conference posters (Paper2Poster). Use this skill for tasks involving paper dissemination, conference preparation, creating explorable academic homepages, generating video abstracts, or producing print-ready posters from LaTeX or PDF sources.
Astro-specific performance optimizations for 95+ Lighthouse scores. Covers critical CSS inlining, compression, font loading, and LCP optimization. Use when optimizing Astro site performance, improving Astro Lighthouse scores, or configuring astro-critters. Do NOT use for non-Astro sites (use perf-web-optimization or core-web-vitals) or running Lighthouse audits (use perf-lighthouse).
Run Lighthouse audits locally via CLI or Node API, parse and interpret reports, and set performance budgets. Use when measuring site performance, understanding Lighthouse scores, setting up budgets, or integrating audits into CI. Triggers on: lighthouse, run lighthouse, lighthouse score, performance audit, performance budget. Do NOT use for fixing specific performance issues (use perf-web-optimization or core-web-vitals) or Astro-specific optimization (use perf-astro).
Optimize web performance: bundle size, images, caching, lazy loading, and overall page speed. Use when site is slow, reducing bundle size, fixing layout shifts, improving Time to Interactive, or optimizing for Lighthouse scores. Triggers on: web performance, bundle size, page speed, slow site, lazy loading. Do NOT use for Core Web Vitals-specific fixes (use core-web-vitals), running Lighthouse audits (use perf-lighthouse), or Astro-specific optimization (use perf-astro).
Create research posters using HTML/CSS that can be exported to PDF or PPTX. Use this skill ONLY when the user explicitly requests PowerPoint/PPTX poster format. For standard research posters, use latex-posters instead. This skill provides modern web-based poster design with responsive layouts and easy visual integration.
Cheminformatics toolkit for fine-grained molecular control. SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints, substructure search, 2D/3D generation, similarity, reactions. For standard workflows with simpler interface, use datamol (wrapper around RDKit). Use rdkit for advanced control, custom sanitization, specialized algorithms.
React composition patterns that scale. Use when refactoring components with boolean prop proliferation, building flexible component libraries, or designing reusable APIs. Triggers on tasks involving compound components, render props, context providers, or component architecture. Includes React 19 API changes. Do NOT use for React/Next.js performance optimization (use react-best-practices instead).
Senior React Native and Expo engineer for building production-ready cross-platform mobile apps. Use when building React Native components, implementing navigation with Expo Router, optimizing list and scroll performance, working with animations via Reanimated, handling platform-specific code (iOS/Android), integrating native modules, or structuring Expo projects. Triggers on React Native, Expo, mobile app, iOS app, Android app, cross-platform, native module, FlatList, FlashList, LegendList, Reanimated, Expo Router, mobile performance, app store. Do NOT use for Flutter, web-only React, or backend Node.js tasks.
Complete Shopify development reference covering Liquid templating, OS 2.0 themes, GraphQL APIs, Hydrogen, Functions, and performance optimization (API v2026-01). Use when working with .liquid files, building Shopify themes or apps, writing GraphQL queries for Shopify, debugging Liquid errors, creating app extensions, migrating from Scripts to Functions, or building headless storefronts. Triggers on "Shopify", "Liquid template", "Hydrogen", "Storefront API", "theme development", "Shopify Functions", "Polaris". Do NOT use for non-Shopify e-commerce platforms.
Create and present web-based slides for developers using Markdown, Vue components, code highlighting, animations, and interactive features. Use when building technical presentations, conference talks, or teaching materials.
Deploy applications and websites to Vercel. Use when the user requests deployment actions like "deploy my app", "deploy and give me the link", "push this live", or "create a preview deployment". Do NOT use for deploying to Netlify, Cloudflare, or Render (use their respective skills).
Deploy and configure applications on Vercel. Use when deploying Next.js apps, configuring serverless functions, setting up edge functions, or managing Vercel projects. Triggers on Vercel, deploy, serverless, edge function, Next.js deployment.
Vue 3 Composition API, script setup macros, reactivity system, and built-in components. Use when writing Vue SFCs, defineProps/defineEmits/defineModel, watchers, or using Transition/Teleport/Suspense/KeepAlive.
Apply VueUse composables where appropriate to build concise, maintainable Vue.js / Nuxt features.
Audit and improve web accessibility following WCAG 2.1 guidelines. Use when asked to "improve accessibility", "a11y audit", "WCAG compliance", "screen reader support", "keyboard navigation", or "make accessible". Do NOT use for SEO (use seo), performance (use core-web-vitals), or comprehensive site audits covering multiple areas (use web-quality-audit).
Comprehensive web quality audit covering performance, accessibility, SEO, and best practices in a single review. Use when asked to "audit my site", "review web quality", "run lighthouse audit", "check page quality", or "optimize my website" across multiple areas at once. Orchestrates specialized skills for depth. Do NOT use for single-area audits — prefer core-web-vitals, web-accessibility, seo, or web-best-practices for focused work.
Core skill for the deep research and writing tool. Write scientific manuscripts in full paragraphs (never bullet points). Use two-stage process with (1) section outlines with key points using research-lookup then (2) convert to flowing prose. IMRAD structure, citations (APA/AMA/Vancouver), figures/tables, reporting guidelines (CONSORT/STROBE/PRISMA), for research papers and journal submissions.
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
Use when building, debugging, packaging, or publishing browser userscripts for Tampermonkey or ScriptCat, including GM APIs, metadata blocks, permission issues, @match/@grant/@connect setup, ScriptCat background or scheduled scripts, UserConfig blocks, or subscription workflows.
Write and critique viral hooks for short-form video: the opening 1 to 3 seconds that decide whether anything else gets seen. Use this when you need a batch of hook ideas for a video, want to make a weak opening line stronger, are picking which hook archetype fits an idea, or want a critique of a draft hook against proven patterns. Covers the three-layer hook (visual, verbal, on-screen text), the named-creator frameworks (Kallaway, MrBeast, Hormozi, Brunson, Koe, Welsh, Bush, Galloway), scroll-stopping hook tactics, and the anti-patterns that tank first-three-seconds retention. Works across TikTok, Reels, and Shorts. Pattern-based guidance that improves the odds. It does not guarantee virality."
Generate short-form video ideas at volume and stop the blank-page problem for good. Use whenever someone says they're stuck for ideas, asks for 20 TikTok ideas or Reels ideas or YouTube Shorts ideas for their niche, wants a content brainstorm, needs help building a content pillar system or content matrix, wants to turn one idea into 5 angles, asks what to post this week, or wants a real idea generator workflow instead of staring at a notes app. Runs the systems prolific creators actually use: pillars, mining (comments, Reddit, search autocomplete, competitor outliers), repurposing, evergreen vs trend balance. Pattern-based guidance grounded in how short-form ideation tends to work; never run out of ideas is the goal, virality is not promised.
Brainstorm and write high-retention short-form video and carousel content for TikTok, Reels, and YouTube Shorts. Use whenever someone wants viral hook ideas, a video script or outline, content concepts for a product or topic, or wants to critique and improve a draft hook or script. Works for any storytime, listicle, carousel, or meme. Produces several diverse hook options from proven patterns, structures scripts for retention (hook, escalation, payoff, CTA), and adapts to each platform. Pattern-based guidance grounded in how short-form tends to perform; it improves the odds, it does not guarantee virality."
Write a tiktok script, a tiktok hook, or a fresh tiktok video idea shaped for how the FYP actually ranks content. Use when someone asks for a tiktok hook for X, wants a script made tiktok-shaped, asks whether a clip is a tiktok or a Reel, wants to improve a tiktok video they drafted, or wants to know what tiktok trends are worth riding this week. Covers the tiktok algorithm signals (user interactions, video information, device and account), completion-rate math by length, trending sound timing, duets, stitches, TikTok Shop pacing, and the AI disclosure regime. Pattern-based guidance for viral tiktok content; it improves the odds of landing on fyp, it does not promise virality."
Write captions, on-screen text, hashtags, and CTAs for short-form video that earn saves and sends without tripping engagement-bait penalties. Use when someone asks for a viral caption, an instagram caption or tiktok caption or video caption, wants to fix a weak cta or call to action, asks about hashtag strategy and whether to add hashtags, wonders what the right pinned comment or comment seeding play is, or needs a gut check on whether their copy is engagement bait. Covers caption length sweet spots per platform, the first-line cutoff, on-screen text patterns for muted watching, native versus cross-posted copy, how hashtags actually work now, send-driving and save-driving CTAs, pinned comment tactics, and the anti-patterns that suppress reach. Pattern-based guidance grounded in how captions and CTAs tend to perform; it improves the odds, it does not guarantee virality.
Write and diagnose YouTube Shorts that hold attention on the Shorts Feed and route viewers into your long-form. Use when someone wants a shorts script, a shorts hook tuned for VVSA and the first 3 seconds, a fix for a flopping short, a read on whether to link a short to a long-form video, or a plan to build the shorts to long form funnel for their channel. Covers what the youtube shorts algorithm rewards now that the Shorts feed runs separately from long-form, how shorts retention is measured, and the youtube shorts strategy choices that move RPM (licensed music split, Creator Pool math, Engaged Views). Pattern-based viral shorts guidance grounded in how shorts tend to perform.
Plan, write, and diagnose Instagram Reels that earn cold-audience reach. Use whenever someone wants a reels script or reels hook for a specific Reel, is debugging why a Reel flopped, wants to know if a draft is worth testing with Trial Reels before going public, or needs a reels caption tuned for the post-hashtag instagram algorithm. Built around what Mosseri has publicly named as the signal hierarchy (watch time, sends per reach, likes per reach), the Trial Reels test-then-publish loop, the Original Content Guidelines and 30-day recovery window, the Edits app, and Reels Insights metrics (skip rate, share rate, followers from this post). Covers a Reels-specific reels strategy: send-driving CTAs, originality without watermarks, audio licensing by account type, captions as the primary SEO signal, and the anti-patterns that quietly cap distribution. Pattern-based guidance, not a virality promise.
> Audit the health of a PostHog project's data warehouse sources and syncs — find every broken or degraded source connection, sync schema, and webhook channel. Use when the user asks "why are my imports failing?", "what's broken with my sources?", "why is my warehouse data stale?", or wants a one-shot triage of source/sync health before deciding where to dig in. Produces a prioritized report grouped by severity, with recommended next steps. For materialized-view health use `auditing-warehouse-view-health`; for a single failing sync use `diagnosing-failed-warehouse-syncs`.
> Author error tracking alerts that fire when an issue is created, reopened, or starts spiking. Use when the user asks to set up error notifications, route exceptions to Slack/webhook/Linear, or evaluate which error events are worth alerting on. Covers trigger-event selection, integration choice, dedup against existing alerts, and shipping with the canonical message body shape.
> Analyze the most expensive users in AI observability and explain why they cost so much. Use when the user asks about top spenders, expensive users, per-user LLM cost, user-level cost drivers, or patterns behind high AI observability spend.
> Audit the health of a PostHog project's materialized views (saved queries) — find every failed materialization and flag unused or stale materialized views that cost storage and compute. Use when the user asks "which of my views are broken?", "why is this materialized view failing?", "are any of my views wasting compute?", or wants a one-shot triage of view health. For source/sync health use `auditing-warehouse-source-health`.
> Build a new dashboard, or update an existing one, from a set of insights — the same job the in-app assistant does with its upsert-dashboard tool, but over MCP. Use when a user asks to create a dashboard, put several metrics/charts together on one page, assemble a dashboard for a topic (product analytics, retention, revenue, activation, etc.), or add/remove/replace insights on a dashboard they already have. Covers deciding create vs update, reusing existing insights vs creating new ones, and using PostHog's vetted dashboard templates as reference for what a strong dashboard on a topic looks like.
> Clarify how to visualize change over a time range before building a trend. Use whenever the user asks how much something changed, grew, dropped, improved, or regressed between two points or periods — "how much did X change from A to B", "before vs after", "start vs end", "week over week", "compare this month to last", "change over time" — or mentions a "slope chart" / (a line, every interval) versus just the two endpoints (a slope, start vs end). Ask which they want, then render it. Not for choosing a saved insight ChartDisplayType in the insight editor.
Determine when a PostHog code change reached a given environment by reading the hidden GIT deploy annotations in the project and correlating them with the merge commit on GitHub. Use when PostHog staff ask "when was X deployed", "is my change live in the US/EU yet", "has my PR shipped", "did the fix roll out to prod-us", or otherwise want to know whether/when a commit, PR, or feature went out to a region. Do not answer deploy-timing questions from event/data volume alone — that only shows when data changed, not when code shipped.
> Copy a PostHog endpoint (a saved HogQL/insight query exposed as an API route) to another project in the same organization, or duplicate it under a new name in the same project. Use when the user wants to duplicate an endpoint, promote an endpoint from staging to production, replicate an endpoint's query/variables/freshness config in another workspace, or clone an endpoint to iterate on it. Unlike feature flags and experiments, endpoints have NO native cross-project copy tool — this skill covers the read-then-recreate flow (endpoint-get then endpoint-create), the active-project switching it requires, name-collision checks, and the safe defaults (land unmaterialised in the target, verify with endpoint-run). Does not cover editing endpoint versions (see managing-endpoint-versions) or authoring a brand-new endpoint from scratch (see creating-an-endpoint).
> Author continuously-running online evaluations in PostHog AI observability, grounded in a real failure mode you've identified. Use when the user wants an evaluation that automatically scores new generations or whole traces going forward — "create an eval to catch X", "continuously check that responses do Y", "turn this failure into an eval". Covers choosing the target and eval type (hog / llm_judge / sentiment), configuring a provider, model, and usable provider key for an llm_judge eval, scoping which generations trigger it via conditions (property filters + rollout sampling), creating it disabled, verifying scope, and enabling. Finding and ranking the failure modes worth evaluating is its own job — use exploring-ai-failures first. To debug or manage evaluations that already exist, use exploring-llm-evaluations.
>- Debug, support, and build PostHog Surveys across the backend and all five SDKs (web/posthog-js, iOS, Android, Flutter, React Native). Use whenever a Surveys support ticket is pasted ("survey not showing", "fewer responses than expected", "responses disappeared", "survey shows on wrong platform"), when diagnosing why a survey does or doesn't display, or when doing survey feature work that must ship across SDKs. Covers the eligibility pipeline, cross-SDK feature parity, the known-cause catalog, read-only diagnostic queries, staff access, and the customer-reply style guide.
> Find where an AI/LLM application is failing in production and surface the failure patterns, working from real traces. Use when someone wants to understand what's going wrong with an AI feature, find and categorize failure modes, triage errors, or investigate quality issues (wrong answers, ignored instructions, hallucinations, tool misuse) — "what's failing in my agent", "surface error patterns", "why are the responses bad", "find the common failure modes", "what should I fix next". Covers scoping to one use case, finding failing traces by whichever signal fits the context (code errors, metric outliers, trace-type slices, manual review, existing-eval spikes, clustering), and reading them into a ranked failure taxonomy.
> Explore PostHog MCP intent clusters — agent goals grouped by semantic similarity, with each cluster's tool distribution and error rates, plus the tool-centric pivot (capture rate per intent, discovery rate against the advertised catalog, description fit, tool overlaps). Use when the user asks "what are agents trying to do with the MCP?", "group the intents", "which goals fail most?", "what does each cluster route to?", "when agents have this intent do they find my tool?", "which tools get mixed up?", wants to recompute the clustering, or pastes an MCP analytics intent-clustering URL.
> Investigate individual PostHog MCP sessions — the sequence of tool calls a single agent made in one run, what it was trying to do, and where it went wrong. Use when the user asks "what did this MCP session do?", "show me the tool calls for session X", "what was the agent's goal?", "which sessions had errors?", "who is connecting to my MCP?", or pastes an MCP analytics sessions URL.
> Investigate the quality of PostHog MCP tool calls — error rates, latency, reach, and which tools are failing or slow. Use when the user asks "which MCP tool has the highest error rate?", "what's the slowest tool?", "which tools fail most often?", "how reliable is tool X?", wants a tool-quality matrix, or pastes an MCP analytics tool-quality / dashboard URL and asks what it shows.
> Starting point for exploring how a PostHog MCP server's tools are used — routes a broad question to the typed tool that answers it. Use when the user asks "how is my MCP doing?", "what should I look at?", "explore my tool calls", "who uses my MCP tools?", "what are agents doing with the MCP?", or pastes an MCP analytics URL without a specific question. Offers a menu of questions, each backed by a query tool, then hands off to the focused skill.
> How to explore and make sense of PostHog Signals scouts — the scheduled agents that scan a project and write reports into the Signals inbox. Use when a user wants to understand what scouts they have, how each one is behaving, and whether the fleet is actually working. Covers surveying the fleet and its schedules, reading recent scout runs and drilling into a single run's reasoning, inspecting the durable scratchpad memory the fleet has built up, tracing a run to the reports it wrote or edited, and assessing a scout's health and performance over time (cadence, success rate, report rate, signal-to-noise). Read-only and exploratory — to write or tune a scout, use `authoring-scouts` instead. Trigger on "what are my scouts doing", "how is my <x> scout performing", "show me recent scout runs", "why did this scout find/report nothing", "what has the fleet learned", "explore scout run <id>", "is my scout working".
Identify, measure, and exclude bot / crawler / AI-agent traffic in PostHog web and product analytics using the traffic classification surface (the isLikelyBot / getTrafficType HogQL functions and the $virt_* virtual properties). Use when the user asks to "exclude bots", "filter out crawlers", "remove bot traffic from my numbers", "how much of my traffic is bots / AI crawlers", "is GPTBot / ChatGPT / Claude hitting my site", "break down traffic by human vs bot", or wants clean human-only counts in an insight or dashboard. For the real-time Live tab bot tiles, use exploring-live-traffic instead.
Guides agents through pulling a Replay Vision scanner's observations, reading the findings, and acting on them — summarizing patterns across sessions, drilling into individual recordings, and turning real, corroborated issues into PostHog tasks, insights, or an investigating-replay hand-off.\nTRIGGER when: user wants to pull/read/triage Replay Vision observations, asks \"what has my scanner found\", wants to act on or summarize scanner findings, turn observations into tasks/work, or points at a /replay-vision/<scanner-id> URL.\nDO NOT TRIGGER when: creating or sizing a scanner (use creating-replay-vision-scanners), running a one-off scan you don't then analyse, or authoring a signals scout.
> MCP agent experience with the eval harness, picks the highest-impact tool problem from production data, makes one bounded fix, and keeps it only if before/after scores improve. Use when asked to "improve my MCP", run an MCP improvement campaign, fix tool discoverability or descriptions based on evidence, or prepare an eval-backed PR for a tool change. Every shipped change must carry eval evidence; guardrails below are hard rules.
> triage an incident, or understand what a log stream is saying. Use when the user asks to "check the logs", asks whether a service, deploy, release, or change is working or broke anything, asks why errors are up or what changed, or wants the root cause of failures visible in logs. Routes the logs MCP tools (services overview, pattern mining, before/after pattern diffing, bucketed counts, facets, raw rows) so investigations start from summaries instead of raw rows or hand-written SQL over the logs table.
> whether it's fixed. Use for "who broke master", "why did this test fail in CI", "is this failure my PR's fault or everyone's", "is this test flaky or actually broken", "when did this failure start". Works from the engineering_analytics warehouse views (engineering_analytics_ci_failures, engineering_analytics_ci_job_history) plus the CI failure logs. Not for aggregate CI health, cost, or merge bottlenecks (use diagnosing-ci-and-merge-bottlenecks) and not for building saved insights (use turning-engineering-analytics-into-insights).
Investigates server/infrastructure metric anomalies in PostHog Metrics — from "this metric is rising/dropping/spiking" or a fired alert to a probable cause with evidence. Use when asked why a metric looks wrong (ingestion lag rising, error rate spiking, latency degrading, queue depth growing, throughput dropping), when an alert fires on an OTel/Prometheus metric, or for any incident triage that starts from a metric symptom. Composes characterize-metric-anomaly, query-metrics, and metric-names-list with logs (query-logs) and traces (APM span tools) for cross-signal root-cause correlation.
Create, deploy, and operate Streamlit apps in PostHog via the streamlit-apps MCP tools — create an app, set its source, start and stop its sandbox, poll status, list versions, delete, and share the app with humans via its PostHog URL. Use when asked to "create a streamlit app", "deploy a data app", "ship a dashboard app", "restart/stop my app", "why is my app not running", or "give me a link to the app".
Create and manage PostHog reminders — private, human-paced nudges that fire as in-app notifications on a schedule, optionally linked to a PostHog resource. Use when the user says "remind me to…", wants a one-off or recurring nudge (daily/weekly/monthly/yearly, a cron schedule, or a specific date/time), wants to be reminded to look at a dashboard, insight, experiment, feature flag, survey, notebook, replay, or error, or wants to list, change, or cancel their reminders. Covers when to pick a reminder over an alert or subscription, the one-off vs recurring vs cron schedule field mappings, timezones, and attaching a resource.
Plan a round of user interviews conducted by PostHog''s AI voice agent (a "robo interviewer") — the automated voice-agent interview product. Captures a UserInterviewTopic (who to target, what to ask, framing context, question list) and calls user-interview-topics-create. ONLY trigger when the user clearly wants an AI voice agent to actually run the interview calls (e.g. "set up robo user interviews", "have the voice agent interview these users"). Do NOT trigger for ordinary user research that does not involve the voice agent — finding or shortlisting users to talk to ("who''d be a good fit to interview about Y"), planning questions for a human-run interview, or analysing feedback are audience discovery, handled with normal data queries, not this skill. Also do NOT trigger for uploading a recorded interview audio file or browsing topics with user-interview-topics-list. When intent is ambiguous, first confirm what kind of research it is and whether they want an AI voice agent to conduct it (see Step 0).
> How to author custom ReviewHog skills — the review perspectives, blind-spot checks, and validation criteria that drive ReviewHog's automated PR reviews. Use when a user wants a new review perspective (a specialist lens on their PRs), a custom blind-spot sweep, or their own validation bar for which findings get published. Trigger on "create a ReviewHog perspective", "custom review perspective", "my own blind-spot check", "custom validation criteria", "tune what ReviewHog publishes".
> The general blind-spot check for ReviewHog — the final sweep that runs after every enabled review perspective has reviewed a chunk. Hunts for real, high-value issues that ALL of the perspectives missed, conditioned on what they actually found; returns an empty list over padding.
> The Contracts & Security review perspective for ReviewHog. Verifies that changed code is safe and maintains compatibility — API contracts and breaking changes, injection / authz / data exposure, input validation, and schema / interface alignment. Reports security and contract issues only.
> The Performance & Reliability review perspective for ReviewHog. Verifies that changed code will perform and hold up in production — resource efficiency, error handling and recovery, scalability, and operational readiness. Reports performance and reliability issues only.
> The Logic & Correctness review perspective for ReviewHog. Verifies that changed code does what it is supposed to do — business logic, edge cases, data transformations, and query / data-access correctness. Reports correctness issues only; security and performance are separate perspectives.
> The validation criteria for ReviewHog — the bar for deciding whether a flagged PR issue is worth keeping. Keeps real, user-affecting correctness / security / data-loss / contract / performance problems; drops overengineering, speculation, paranoia, never-gonna-happen edge cases, and style.
> Connect a real Slack workspace to local PostHog Conversations (the SupportHog Slack app) so Slack messages become support tickets and replies post back. Use when the user wants to test the conversations Slack integration locally, hits "Support Slack OAuth client ID is not configured", gets a white screen or "Network error" on the OAuth callback, or asks how to set SUPPORT_SLACK_APP_CLIENT_ID / a tunnel for supporthog Slack events. Covers the Slack app + scopes, the SUPPORT_SLACK_* dynamic settings, and the
> (certifications) on warehouse tables/views, and reviewed table relationships. Use when asked to set up / seed / bootstrap the data catalog or semantic layer, to catalog a project's metrics, to certify or deprecate data sources, to propose or review table joins, or to work through the proposal review queue. To *use* an existing catalog to answer a business-number question, see querying-posthog-data source, relationship proposal, metric drift, review queue.
Claude Skills — questions
Answers built from the skills we actually parsed.