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Found 13,627 Skills
OpenAI Responses API for stateful agentic applications with reasoning preservation. Use for MCP integration, built-in tools, background processing, or migrating from Chat Completions.
Forensic audit of the user's recent Claude Code sessions to surface step-change workflow improvements — not marginal ones. Use when the user asks to "audit my Claude Code sessions", "analyze how I use Claude Code", "find patterns in my usage", "improve my Claude Code workflow", "review my sessions", "find leverage in my setup", or wants to understand where their Claude Code setup is leaking time. Samples dozens of real transcripts, extracts quantitative signal via scripts, uses parallel subagents for deep reads, then synthesizes into a short prioritized report with drafted implementations (new skills, CLAUDE.md rules, hooks, settings diffs) that the user can install directly. Trigger even when the user doesn't say the word "audit" — if they're asking about improving or reviewing their Claude Code habits at scale, use this skill.
Every PostHog resource in one CLI — with offline search, agent-native output, and cross-resource analytics no... Trigger phrases: `check my PostHog feature flags`, `query PostHog events`, `show experiment results in PostHog`, `what errors are spiking in PostHog`, `LLM costs in PostHog`, `is it safe to ramp this flag`, `use posthog`.
This skill should be used when the user asks to "fix my skill" or "audit this skill". Make sure to use this skill whenever the user mentions skill quality, structural issues, broken skills, or skill diagnostics — even if they don't explicitly say "repair-skill". Not for adding features or improving effectiveness — use improve-skill. Not for agents — use repair-agent.
Invoke a Rubber Duck Reviewer subagent to independently critique plans and implementations before proceeding. Use when the agent is about to implement a non-trivial plan (multi-file changes, architectural decisions, security-sensitive logic, database schema changes), after completing a self-contained unit of work (module, endpoint, feature), when stuck or facing repeated failures (same test fails 2+ times, unexpected results), or when the agent wants independent validation of assumptions and design decisions. Triggers on any non-trivial implementation task where independent critique would catch blind spots before they become costly mistakes.
Interactive QA session where users report bugs or issues through conversation, and the agent creates GitHub issues. Explore the codebase in the background to obtain context and domain language. Use when user wants to report bugs, do QA, file issues conversationally, or mentions "QA session".
Use when an agent needs to send outreach, reply to inbound, sign up for a service, or log into a site via the user's autark-provisioned AgentMail inbox. Everything goes through `autark mail`.
Bootstrap skill — teaches the agent how to find and invoke skills. Use when starting any new task or session.
Apiiro CLI commands for querying the Guardian AI agent: ask security questions, get analysis and insights about a repository, and manage repository detection. Use this skill whenever the user wants AI-powered security analysis, security posture review, or wants to ask questions about their codebase's security. Also trigger when they need deep analysis of authentication flows, attack surfaces, or want an AI to explain security concepts. Even without mentioning "apiiro" or "guardian", trigger when the user asks things like "is this code secure?", "what's the attack surface here?", or "explain this vulnerability". For dedicated STRIDE threat modeling of a design or feature spec, use the apiiro-threat-model skill instead. For fixing a known risk, use apiiro-fix.
Validate and auto-repair YAML frontmatter on brain pages. Catches malformed pages before they enter the brain (missing closing
Always-on ambient signal capture. Fires on every inbound message to detect original thinking and entity mentions. Spawn as a cheap sub-agent in parallel, never block the main response.
Primarily the agent's internal-thinking skill — invoke it silently to model a problem, identify trade-offs, and decide what to do, BEFORE asking the user anything or dispatching another skill. Workflow skills call `/culture` as their step-1 reasoning pass; the agent does not surface the dialogue. Only treat this as a user-facing skill when the user has explicitly opted out of writes — phrases like "no writes", "just rubber-duck this", "let's only talk", "/culture". In the user-facing path the output is conversation; the only sanctioned artifact is an opt-in `.cheese/notes/<slug>.md` handoff slug at session end if the user asks for notes. Culture never writes to production code, never commits, never opens PRs. If the dialogue reveals real work, recommend `/mold` (fuzzy → spec) or `/cook` (clear ask → code) and stop. Before `/mold` or `/cook`.