Browse skills

Load code-style rules, make the change described by the current context, then run /finalize for QA and commit. Use for ad-hoc changes when no plan file or improvements backlog governs the work, and when the user asks to "just implement", "implement directly", "implement without a plan", or "apply the change".

Draft, confirm, and post replies to GitHub PR review threads. Handles per-category reply formatting, re-fetches thread resolution state so auto-resolved threads are skipped, and posts via GraphQL. Use when the user asks to "reply to PR threads", "post PR thread replies", or "draft PR reply messages".

Choose an implementation path (trivial or standard) for evaluated findings and dispatch it. Trivial path applies fixes directly; standard path hands off to /turboplan. Use after /evaluate-findings has tagged findings and they need to be implemented, or when the user asks to "resolve findings", "apply evaluated findings", or "dispatch findings to implementation".

HyperFrames CLI tool — hyperframes init, lint, preview, render, transcribe, tts, doctor, browser, info, upgrade, compositions, docs, benchmark. Use when scaffolding a project, linting or validating compositions, previewing in the studio, rendering to video, transcribing audio, generating TTS, or troubleshooting the HyperFrames environment.

Install and wire registry blocks and components into HyperFrames compositions. Use when running hyperframes add, installing a block or component, wiring an installed item into index.html, or working with hyperframes.json. Covers the add command, install locations, block sub-composition wiring, component snippet merging, and registry discovery.

Create video compositions, animations, title cards, overlays, captions, voiceovers, audio-reactive visuals, and scene transitions in HyperFrames HTML. Use when asked to build any HTML-based video content, add captions or subtitles synced to audio, generate text-to-speech narration, create audio-reactive animation (beat sync, glow, pulse driven by music), add animated text highlighting (marker sweeps, hand-drawn circles, burst lines, scribble, sketchout), or add transitions between scenes (crossfades, wipes, reveals, shader transitions). Covers composition authoring, timing, media, and the full video production workflow. For CLI commands (init, lint, preview, render, transcribe, tts) see the hyperframes-cli skill.

Capture a website and create a HyperFrames 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.

Execute multi-level exploratory testing of the app covering basic functionality, complex operations, adversarial testing, and cross-cutting scenarios. Deeper than /smoke-test. Use when the user asks to "exploratory test", "test thoroughly", "test all scenarios", "deep test", "test edge cases", "test everything", "break it", or "find bugs by testing".

Draft, confirm, and post a single conversational reply to GitHub PR conversation comments (issue comments). The reply addresses all tracked items in one natural-prose message. Use when the user asks to "reply to PR conversation", "post PR conversation replies", or "draft PR conversation messages".

Scans an existing codebase and generates project-specific skills that capture inferred conventions such as naming, file organization, framework usage, data access, error handling, and testing style. Writes into the project's chosen skill directory (e.g., `.claude/skills/`, `.agents/skills/`, or a custom path). Use when the user asks to "extract skills from the codebase", "create project skills", "infer project conventions as skills", "codify patterns as skills", or "mine the repo for best practices".

Convert input into clean, structured, hierarchical bullet points for summarization, note-taking, and structured thinking.

Production-ready patterns for integrating frontend applications with backend APIs, including race condition handling, request cancellation, retry strategies, error normalization, and UI state management.

Native agent-to-agent language for compact multi-agent messaging. A shared tongue agents speak directly, not a translation layer. 340+ atoms across 7 domains; 3x smaller than natural language.

AI-powered browser automation — navigate sites, fill forms, extract structured data, log in with stored credentials, and build reusable workflows.

NCAA cross country and track & field athlete data via TFRRS (tfrrs.org) and news via The Stride Report. Fetch athlete profiles including all personal records (PRs), eligibility year, school, full season-by-season results history, and XC/TF news. Zero config, no API keys. Use when: user asks about NCAA cross country, NCAA track and field, college running, TFRRS athlete profiles, personal records, PRs, XC or TF season results, individual athlete performance history, or XC/TF news. Don't use when: user asks about professional track, Diamond League, or other sports — use nfl-data, nba-data, wnba-data, nhl-data, mlb-data, golf-data, cfb-data, cbb-data, tennis-data, fastf1, or volleyball-data. For betting use polymarket or kalshi.

Compiles any research input — PDF papers, GitHub repositories, experiment logs, code directories, or raw notes — into a complete Agent-Native Research Artifact (ARA) with cognitive layer (claims, concepts, heuristics), physical layer (configs, code stubs), exploration graph, and grounded evidence. Use when ingesting a paper or codebase into a structured, machine-executable knowledge package, building an ARA from scratch, or converting research outputs into a falsifiable, agent-traversable form.

Records research provenance as a post-task epilogue, scanning conversation history at the end of a coding or research session to extract decisions, experiments, dead ends, claims, heuristics, and pivots, and writing them into the ara/ directory with user-vs-AI provenance tags. Use as a session epilogue — never during execution — to maintain a faithful, auditable trace of how a research project actually evolved.

Pre-install security scanner for AI agent skills. 7.5% of 14,706 skills are malicious. Audit before you trust.

Performs ARA Seal Level 2 semantic epistemic review on Agent-Native Research Artifacts, scoring six dimensions (evidence relevance, falsifiability, scope calibration, argument coherence, exploration integrity, methodological rigor) and producing a constructive, severity-ranked report with a Strong Accept-to-Reject recommendation. Use after Level 1 structural validation passes, when an ARA needs an objective epistemic critique before publication or release.

Migrate legacy files in .turbo/ to current formats. Covers plans and shells (layout split, frontmatter normalization, prompt-plan index cleanup) and improvements.md (legacy `trivial`/`standard` Type values rewritten to `direct`/`plan`). Use when the user asks to "migrate turbo files", "migrate turbo", "migrate turboplans", "migrate turbo plans", "upgrade plan format", "add frontmatter to plans", "convert old plans", or "migrate improvements".