Agent Skills
Instruction packs that give your AI agent know-how. Three different kinds — pick the right one below.
✦ Standalone skills4,610
Self-contained. Install one into any project and it works on its own — no other software needed.
🧰 Tool add-ons1,006
Come bundled with a specific tool and only work together with it — they teach your agent how to operate that tool.
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1,560 standalone skillsfeature-flags-ruby
★ 49by posthog
PostHog feature flags for Ruby applications
feature-flags-rust
★ 49by posthog
PostHog feature flags for Rust applications
feature-flags-web
★ 49by posthog
PostHog feature flags for Web (JavaScript) applications
integration-react-tanstack-router-file-based
★ 49by posthog
PostHog integration for React applications using TanStack Router with file-based routing
integration-angular
★ 49by posthog
PostHog integration for Angular applications
integration-astro-static
★ 49by posthog
PostHog integration for static Astro sites using SSG
integration-astro-view-transitions
★ 49by posthog
PostHog integration for Astro with ClientRouter view transitions
llm-analytics-setup
★ 49by posthog
PostHog LLM analytics for all supported providers
logs-datadog
★ 49by posthog
PostHog logs for Datadog
logs-go
★ 49by posthog
PostHog logs for Go
logs-java
★ 49by posthog
PostHog logs for Java
logs-nextjs
★ 49by posthog
PostHog logs for Next.js
logs-nodejs
★ 49by posthog
PostHog logs for Node.js
omnibus-instrument-error-tracking
★ 49by posthog
Add PostHog error tracking to capture and monitor exceptions. Use after implementing features or reviewing PRs to ensure errors are tracked with stack traces and source maps. Also handles initial PostHog SDK setup if not yet installed.
omnibus-instrument-feature-flags
★ 49by posthog
Add PostHog feature flags to gate new functionality. Use after implementing features or reviewing PRs to ensure safe rollouts with feature flag controls. Also handles initial PostHog SDK setup if not yet installed.
omnibus-instrument-integration
★ 49by posthog
Add PostHog SDK integration to your application. Use when setting up PostHog for the first time or reviewing PRs that need PostHog initialization. Covers SDK installation, provider setup, and basic configuration for any framework.
omnibus-instrument-llm-analytics
★ 49by posthog
Add PostHog LLM analytics to trace AI model usage. Use after implementing LLM features or reviewing PRs to ensure all generations are captured with token counts, latency, and costs. Also handles initial PostHog SDK setup if not yet installed.
omnibus-instrument-logs
★ 49by posthog
Add PostHog log capture to track application logs. Use after implementing features or reviewing PRs to ensure meaningful log events are captured with structured properties. Also handles initial OTLP exporter setup if not yet configured.
omnibus-instrument-product-analytics
★ 49by posthog
Add PostHog product analytics events to track user behavior. Use after implementing new features or reviewing PRs to ensure meaningful user actions are captured. Also handles initial PostHog SDK setup if not yet installed.
posthog-debugger
★ 49by posthog
Debug and inspect PostHog implementations on any website. Use this skill when a user wants to understand how PostHog is implemented on a page, troubleshoot tracking issues, verify configuration, check what events are being sent, or audit a PostHog setup. Works with Chrome DevTools MCP and Playwright MCP to inspect live websites.
posthog-onboarding
★ 49by posthog
Help existing PostHog customers improve their PostHog instance. Triggers on "help [customer] improve their PostHog setup", "audit [company]'s PostHog instance", "create tracking plan for [company]", "design data schema for [customer]", or requests to improve analytics coverage, fix instrumentation gaps, expand PostHog usage, or build better insights for customers already using PostHog. Use when working with a customer who already has PostHog installed.
analyzing-experiment-session-replays
★ 49by posthog
Analyze session replay patterns across experiment variants to understand user behavior differences. Use when the user wants to see how users interact with different experiment variants, identify usability issues, compare behavior patterns between control and test groups, or get qualitative insights to complement quantitative experiment results.
assessing-heatmaps
★ 49by posthog
Assesses what a page's heatmap is telling you and recommends concrete changes. Pulls click / rageclick / scroll-depth data for a URL, names the hot elements by cross-referencing autocapture events on the same page, and can create a saved heatmap the user opens in PostHog, then summarizes the behavior and proposes improvements.\nTRIGGER when: user asks what a heatmap shows, why people aren't clicking something, where users rage-click, how far they scroll, what to change on a page based on heatmap
auditing-warehouse-data-health
★ 49by posthog
Audit the health of a PostHog project's data warehouse — find every broken or degraded pipeline item across sources, sync schemas, materialized views, batch exports, and transformations. Use when the user asks "what's broken in my warehouse?", "give me a health check", "audit my data pipeline", "why are some dashboards stale?", or wants a one-shot triage summary before deciding where to spend time. Produces a prioritized report of issues grouped by severity and type, with recommended next steps.
authoring-signals-scouts
★ 49by posthog
How to author, edit, and adapt PostHog Signals scouts — the scheduled agents that scan a project and emit findings into the Signals inbox. Use when a user wants to customize a canonical scout for their own setup (narrow its scope, retune its thresholds, add disqualifiers), tweak a scout's schedule or dry-run posture, or write a brand-new scout from scratch for a specific use case (a custom event, a product surface no canonical scout covers). Covers the scout SKILL.md anatomy, the emit contract,
configuring-experiment-analytics
★ 49by posthog
Configures the analytics side of a PostHog experiment — exposure criteria (default `$feature_flag_called` vs custom exposure events), primary and secondary metrics, the supported metric types (count, sum, ratio with `math` and `math_property`, retention with `retention_window_start` and `start_handling`), multivariate user handling ("Exclude" vs "First seen variant"), and how to read results once the experiment is live. Use when the user adds or edits a primary or secondary metric (e.g. "add a s
experiment-audit
★ 49by posthog
Audit a PostHog A/B experiment for a customer — verify config, exposure, attribution, and metrics. Trigger phrases include \"audit [customer]'s experiment\", \"audit the [name] experiment\", \"check experiment setup for [customer]\", \"validate this A/B test\", or any request to review whether an experiment is correctly wired up. Assumes you already have MCP access to the customer's project (typically via the impersonation flow set up by the `impersonate-audit` wrapper that ships with this plugi
configuring-experiment-rollout
★ 49by posthog
Configures the rollout shape of a PostHog experiment — the variant split (50/50, 80/20, A/B/C ratios), the overall rollout percentage that gates how many users enter the experiment, and the disambiguation when a percentage like "roll out to 25%" could mean either. Use when the user mentions a rollout percentage, variant split, or traffic distribution; gives a ratio like 60/40, 70/30, or 80/20; asks "who sees the test variant?"; wants to increase, decrease, or change the rollout or split on a dra
consuming-endpoints-from-client-code
★ 49by posthog
Wire a PostHog endpoint into a client app or SDK. Covers fetching the OpenAPI spec, generating a typed client with openapi-generator or @hey-api/openapi-ts, sending the right auth header, shaping the variables payload (HogQL code_name vs insight breakdown property), handling rate-limit and materialised-endpoint error responses. Use when the user says "how do I call my endpoint", "generate a client for this", or "what auth header do I use".
creating-ai-subscription
★ 49by posthog
Create a recurring AI-generated PostHog report — schedule a free-text prompt to run on a cron, with the LLM-synthesized markdown delivered to email or Slack on each tick. Use when the user wants a recurring AI summary of X on any cadence (daily, weekly, monthly, yearly) rather than a one-off report. (To attach an AI summary to an existing insight/dashboard subscription instead of a free-text prompt, see `managing-subscriptions` and its `summary_enabled` option.)