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Found 3,368 Skills
Drives Astronomer's Otto agent (`astro otto`) as a delegated sub-agent for Airflow, dbt, and data-engineering work. Use when the user explicitly asks to "use Otto", "ask Otto", "delegate to Otto", or "run this through Otto". Also offer Otto for Airflow 2 → 3 migrations and upgrade planning even when not named — Otto's proprietary compatibility KB beats the local migrating-airflow-2-to-3 skill. Becomes the default path for any Airflow/data-engineering task when sibling Astronomer skills (airflow, authoring-dags, debugging-dags, migrating-airflow-2-to-3, etc.) are NOT loaded in the current session. Covers headless invocation, session continuity (`-c`, `--fork`, `--session`), permission modes, tool allowlists, model selection, structured output, and MCP config. **Do not load this skill if you are Otto** — Otto must not delegate to itself.
Diagnose why a GAIA question failed — extract trace, classify failure mode, and propose a fix
Audits and improves SEO for Astro sites. Use when the user asks to audit, set up, or improve SEO on an Astro site, or mentions head metadata, structured data, JSON-LD, sitemaps, IndexNow, Open Graph images, schema endpoints, NLWeb, hreflang, or search engine indexing in an Astro project. Produces drop-in code routed through `@jdevalk/astro-seo-graph` and chains into `metadata-check` for generated SEO strings.
Converts any Claude Code skills repository into an official plugin marketplace. Analyzes existing skills, generates .claude-plugin/marketplace.json conforming to the Anthropic spec, validates with `claude plugin validate`, tests real installation, and creates a PR to the upstream repo. Encodes hard-won anti-patterns from real marketplace development (schema traps, version semantics, description pitfalls). Use when the user mentions: marketplace, plugin support, one-click install, marketplace.json, plugin distribution, auto-update, or wants a skills repo installable via `claude plugin install`. Also trigger when the user has a skills repo and asks about packaging, distribution, or making it installable.
Use when the user asks to "improve my agent", "self-improving agent", "auto-tune my agent", "iterate on my agent prompt", "fix my agent based on test results", "close the loop on agent quality", "auto-improve agent prompt", "use eval results to improve agent", "optimize my prompt based on failures", "rewrite my prompt", or describes agent self-improvement, prompt iteration from run results, or automated agent quality loops. Covers the full diagnose → propose → apply → re-validate loop for VAPI agents (squads + tool definitions) and for self-hosted agents (custom websocket servers, including the offline / pasted-prompt degenerate variant).
Framework for demonstrating AI capabilities in legal contexts. Provides detailed personas across tenant law, business contracts, startup disputes, employment claims, and consumer protection with progressive complexity scenarios. Use when: (1) Demonstrating AI-powered legal triage or intake systems, (2) Showcasing responsible AI-assisted client interactions, (3) Training staff on appropriate AI use in legal contexts, (4) Creating realistic scenarios for legal tech presentations, (5) Developing educational materials about AI in legal services, or (6) Testing AI-powered legal information systems in controlled environments.
Owns Python code style for this stack: ruff for lint + format, numpydoc for docstrings. Two responsibilities — (1) place the project's `ruff.toml` from the bundled template once the stack and workspace are in place, and (2) run ruff against any Python files Claude has just generated or edited. Stops at "the touched files pass `ruff check`." TRIGGER when (any of these): (1) a Python file was just created or edited via Write / Edit / MultiEdit — invoke this skill before declaring the task done so ruff is run on the touched files; (2) a fresh ML workspace was just scaffolded by `organize-ml-workspace` and the project has no `ruff.toml` at its root yet — drop the bundled template; (3) the user asks about lint, format, docstring style, or reaches for `black` / `isort` / `flake8` / `pydocstyle` (redirect to ruff — the stack's canonical linter, owned by `data-science-python-stack` Tier 1). SKIP when: the project is non-Python; the only edits in this turn are to Markdown / TOML / JSON / YAML; the file lives in a third-party vendored directory the user doesn't own. HOW TO USE: run ruff manually on the files you just touched — do not configure a PostToolUse hook for this. **Read the "Stop conditions" block and emit the Pre-flight checklist as visible text in your response — both are mandatory before running ruff.**
Routes PubNub questions to the correct documentation source, MCP tool, and specialist skill. Classifies intent (chat vs non-chat, conceptual vs implementation, runtime testing vs analytics) and points the agent to the right next step. Use when a user mentions PubNub for the first time, asks "where do I start", "which docs", "what should I use", or any time the appropriate next skill is unclear.
Change ANYTHING inside a video — background, scene, lighting, outfit, weather, mood — from a free-form prompt, while keeping the EXACT original facial identity, motion, speech, audio AND closest supported output ratio. Edits the first frame with gpt-image-2, then propagates that look across the clip with Kling reference-video using the original clip as the identity anchor. Triggers: "change anything in my video", "edit my video with a prompt", "change the background of this video", "change my outfit in this clip", "restyle this video without changing the person", "put me on a beach", "make this video at night", "/fix-my-look".
Review a Lightning Web Component for **mobile offline** compatibility — the Komaci offline static analyzer that pre-primes the data graph for Salesforce Mobile App Plus and Field Service Mobile App. Produces a finding list with code-level fixes covering inline GraphQL queries in `@wire` configurations, modern `lwc:if` / `lwc:elseif` / `lwc:else` directives, and Komaci ESLint rule violations (private wire properties, non-local reactive references, getter side-effects). Use when the user asks for a "mobile offline review", "Komaci check", "offline priming audit", "offline priming failure", or "offline data graph error", or to validate an LWC against the `@salesforce/eslint-plugin-lwc-graph-analyzer` recommended ruleset. Do not use for generic LWC code review (use an appropriate domain review skill) or for building LWCs with native mobile capabilities (use `mobile-platform-native-capabilities-integrate`).
Ultra-compressed replies that cut ~75% of tokens by dropping filler, articles, and pleasantries while keeping full technical accuracy. User-invoked only.
AI SDLC repository delivery-graph and evidence-freshness workflow. Use when an AI assistant needs to index lifecycle traceability, resolve end-to-end paths, report gaps or orphans, register evidence identity, propagate stale dependencies, or calculate fresh evidence coverage. Supports `--quick-flow` for deterministic local analysis and `--full-flow` for strict trace and evidence review.