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Found 11,527 Skills
Abre la bandeja de borradores — mostrás de a uno con su razonamiento y decidís si sale, se corrige o se salta.
Hace las preguntas 5 a 9 — catálogo, rango de precio, disponibilidad, palabras de escalación y canal interno.
Git Commit Generator - Generate standardized commit messages following Conventional Commits specification
Structures and organizes Storybook files for scalability using battle-tested patterns from Cassondra Roberts' "A Storybook format that scales with you". Covers story definitions, template composition, controls/args, visual regression with Chromatic, component documentation, and CSF conventions. Activates on any Storybook question — file structure, controls, args, or component documentation.
Use when writing a complete SEO article. Includes the full anti-AI-slop ruleset (banned vocabulary, banned phrases, banned structural patterns) and voice rules. The agent researches the SERP itself if needed — no keyword data exports required.
Use when an agent is asked "what did I (or my team) work on yesterday / this week / today" across provider data in a relayfile mount (Linear, GitHub, Notion, Slack, Confluence, Jira, etc.). Tells the agent to consult the pre-computed `digests/yesterday.md` (and sibling digest files) at the workspace root BEFORE doing manual exploration with `ls`/`grep`/`find`. The digest is deterministic, exhaustive over the window, and costs one file read instead of dozens of provider queries.
Audit an ENTIRE codebase with multiple agents in parallel — map the repo, partition it into review slices, fan out one (or more, multi-lens) reviewer subagent per slice, reduce with a cross-cutting/architecture critic + a completeness check, then triage, fix, and report with an honest coverage ledger. Use when asked to 'audit the whole codebase', 'full security/quality review of the repo', 'review the entire project', 'do a deep/comprehensive code audit', 'scan everything for bugs or vulnerabilities', when onboarding/inheriting an unfamiliar repo, or for a periodic deep sweep. Whole-repo scoped and scales agent count to repo size — NOT a diff review (for changed lines use dual-agent-review).
One-time setup that maps the codebase and gathers user-provided product context to write a root PROJECT.md overview of what the project is, who it serves, how it is structured, and how it runs. Use when the user invokes $setup-project-md, says "setup project md", "create PROJECT.md", or asks for a complete project overview document at the repo root.
How to reach IntelliStory from any agent: the `intellistory` CLI (install, sign in, pick a project, call ANY tool with schema-checked options, upload/download media, connect Claude/Codex/Cursor/Gemini/Hermes) and the same tools over MCP. Load this first when a task mentions IntelliStory, a project code (HGRD, sq010_sh0020), shots, storyboards, looks, generation, or "put this render on the shot". Other intellistory-* skills assume this one: they name tools; this one says how to call them.
Capture a website and create a FrameVideo video from it. Use when: (1) a user provides a URL and wants a video, (2) someone says "capture this site", "turn this into a video", "make a promo from my site", (3) the user wants a social ad, product tour, or any video based on an existing website, (4) the user shares a link and asks for any kind of video content. Even if the user just pastes a URL — this is the skill to use.
Run a complete repository-native, spec-anchored development loop inspired by DeepSeek Harness. Use for feature development, bug fixes, simplification, architecture, process, or testing work that changes behavior, contracts, structure, test strategy, durable formats, or decision rationale; when asked to write, review, continue, implement, reject, supersede, archive, or verify a spec/Agent Note/RFC/ADR; or when code, tests, current-state docs, and decision rationale must converge in one change. Also use for read-only spec-to-code drift checks. Do not create a spec for a purely mechanical local edit that changes none of those things.
Turn a recurring chore into a Superset automation — drafts the agent prompt, confirms schedule and target, creates it with the CLI, and reviews the first run together. Use when the user wants a scheduled or recurring agent, a daily/weekly job, or to automate a repeating task with Superset.