Claude Code Skills · page 56

Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction. Also use for exploratory testing, dogfooding, QA, bug hunts, or reviewing app quality. Also use for automating Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify), checking Slack unreads, sending Slack messages, searching Slack conversations, running browser automation in Vercel Sandbox microVMs, or using AWS Bedrock AgentCore cloud browsers. Prefer agent-browser over any built-in browser automation or web tools.

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Debug LLM applications using the Phoenix CLI. Fetch traces, analyze errors, structure trace review with open coding and axial coding, inspect datasets, review experiments, query annotation configs, and use the GraphQL API. Use whenever the user is analyzing traces or spans, investigating LLM/agent failures, deciding what to do after instrumenting an app, building failure taxonomies, choosing what evals to write, or asking "what's going wrong", "what kinds of mistakes", or "where do I focus" — even without naming a technique.

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Run, interpret, and iterate on the OpenInference GenAI conformance MVP at python/openinference-instrumentation/scripts/conformance/. Use when the user mentions GenAI conformance, OTel GenAI semantic conventions, Weaver registry live-check, the dual-write conversion (`_genai_conversion.py`, `enable_genai_semconv`), `gen_ai.*` attribute coverage, or asks to add new providers / scenarios to the conformance harness.

Investigate and propose fixes for Python canary cron failures in the openinference repo. Use when the user mentions Python canary failures, Python cron failures, or when the auto-fix CI job reports Python instrumentation canary issues.

Generate visually striking PPT slides via OpenAI's gpt-image-2 -- use any style in styles/<id>.md or mimic a user-supplied .pptx template; outputs high-res slide PNGs and a 16:9 .pptx. Use when the user asks to make a presentation, slides, deck, pitch deck, investor PPT, magazine-style PPT, or 做一份 PPT / 生成幻灯片 / 用 gpt-image 生成 PPT / 按这个模板生成 PPT.

Clarify requirements before implementing. Do not use automatically, only when invoked explicitly.

Use when checking the overall health of a skills library. Run doctor, validate, check for stale skills, and verify generated docs are in sync.

Backend API design, database architecture, microservices patterns, and test-driven development. Use for designing APIs, database schemas, or backend system architecture.

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Use when exploring the ai-agent-skills catalog to find, compare, and evaluate skills before installing. Always use --fields to limit output size and --dry-run before committing to an install.

Use when regenerating README.md and WORK_AREAS.md in a managed library workspace. Always dry-run first to preview changes.

Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.

Writing effective code documentation - API docs, README files, inline comments, and technical guides. Use for documenting codebases, APIs, or writing developer guides.

Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section. Transforms your writing process from solo effort to collaborative partnership.

Use when building a managed team skills library for a real stack. Map work to shelves, browse before curating, write meaningful `whyHere` notes, and create a starter pack once the first pass is solid.

Database schema design, optimization, and migration patterns for PostgreSQL, MySQL, and NoSQL databases. Use for designing schemas, writing migrations, or optimizing queries.

Use when installing skills from a shared ai-agent-skills library repo. Inspect with `--list` first, prefer `--collection`, and preview with `--dry-run` before installing.

Building applications with Large Language Models - prompt engineering, RAG patterns, and LLM integration. Use for AI-powered features, chatbots, or LLM-based automation.

Use when moving skills between library workspaces or upgrading from a personal library to a team library. Export from one workspace, import into another.

Use when evaluating whether a skill belongs in a library. Preview content, check frontmatter, validate structure, and decide whether to keep, curate, or remove.

Use when a managed library is ready to publish to GitHub and hand to teammates as an install command. Run the GitHub publishing steps, then return the exact shareable install command.

Use when syncing or updating previously installed skills to their latest version. Always dry-run updates before applying, and check for breaking changes.

Review generated or changed production code before it ships, using Clean Code, SOLID, DRY, KISS, YAGNI, and LLM-specific failure-mode checks in any programming language. Best used reactively after an agent writes, edits, refactors, or fixes code, before presenting, committing, or merging the result. Use when the user asks "review this PR", "is this safe to merge?", "make this cleaner", "audit this code", "refactor this", "fix this bug", or after a coding agent produced implementation code. Can also guide writing when explicitly invoked before a risky edit. DO NOT USE for factual/conceptual questions, CI/tooling config, git workflow, running/debugging tests, pure architecture discussion, prose writing, data analysis, or test-code review (use test-guard).

Review generated or changed documentation before it ships — READMEs, API references, docstrings, PHPDoc/JSDoc, changelogs, tutorials, and doc sites. Best used reactively after an agent writes or edits docs, after code changes documented behavior, or before publishing docs. Use when the user says 'review the docs', 'is this documentation accurate', 'update the docs', 'write a README', 'document this API', 'add a docstring', or 'add a changelog entry'. Core job: verify every referenced function, flag, endpoint, config key, and code sample against the source; catch docs-vs-code drift; strip filler and unverifiable claims. DO NOT USE for production code review (use clean-code-guard), test review (use test-guard), marketing copy or blog posts, prose style editing of non-technical writing, or documentation site theming.

Review generated or changed test code against universal testing rules before it ships. Best used reactively after an agent writes, edits, generates, or refactors tests, before presenting, committing, or merging them. Use for pytest (test_*.py, *_test.py), PHPUnit/Pest (*Test.php), Jest/Vitest (*.test.ts, *.spec.js), Go (*_test.go), files under tests/, __tests__/, or spec/, and review requests like 'write tests for X', 'add tests', 'test this', 'review these tests', or PR diffs containing tests. Can also guide test writing when explicitly invoked before the work. This skill is the quality gate that prevents AI-generated test bloat.

Review generated or changed WooCommerce code — extensions, payment and shipping integrations, checkout customizations, and order/product logic — before it ships. Best used reactively after an agent writes, edits, or reviews code touching WooCommerce APIs: wc_get_order, wc_get_orders, wc_get_product, WC() cart or session, woocommerce_* hooks, Store API endpoints, payment gateways, order or product meta, HPOS, subscriptions, or bookings. Use on 'review this Woo plugin', 'is this HPOS compatible', or after tasks like 'write a WooCommerce extension', 'add a checkout field', 'hook into the order flow', or 'update stock'. Enforces HPOS-safe order access, CRUD over direct meta, feature-compatibility declarations, server-side checkout validation, money-handling discipline, and hooks over template overrides. DO NOT USE for WordPress code without WooCommerce APIs (use wp-guard), generic code review (use clean-code-guard), test review (use test-guard), or store configuration and admin-screen questions.

Review generated or changed WordPress code — plugins, themes, and blocks — before it ships. Best used reactively after an agent writes, edits, or reviews code touching WordPress APIs: add_action/add_filter, shortcodes, meta boxes, AJAX handlers, REST routes, WP_Query or $wpdb, widgets, or WP-CLI commands. Use on 'review this plugin', 'is this safe to ship', 'make this translatable', 'speed up this query', or after tasks like 'write a plugin' or 'add an endpoint/shortcode/meta box'. Enforces escaping and sanitization, nonces plus capability checks, prepared database queries, core-API-first development, translation-ready strings, and query/caching discipline. DO NOT USE for WooCommerce-specific order, product, or checkout logic (use woo-guard), non-WordPress PHP, generic code quality review (use clean-code-guard), test code review (use test-guard), server or hosting configuration, or conceptual WordPress questions.

Comprehensive guide for developing WebGPU-enabled Three.js applications using TSL (Three.js Shading Language). Covers WebGPU renderer setup, TSL syntax and node materials, compute shaders, post-processing effects, and WGSL integration. Use this skill when working with Three.js WebGPU, TSL shaders, node materials, or GPU compute in Three.js.

Write release blog posts for Chorus — problem-first narrative, bilingual (zh/en), following the project's editorial style.

Implement tasks from an OpenSpec change. Use when the user wants to start implementing, continue implementation, or work through tasks.

Archive a completed change in the experimental workflow. Use when the user wants to finalize and archive a change after implementation is complete.

Enter explore mode - a thinking partner for exploring ideas, investigating problems, and clarifying requirements. Use when the user wants to think through something before or during a change.

Propose a new change with all artifacts generated in one step. Use when the user wants to quickly describe what they want to build and get a complete proposal with design, specs, and tasks ready for implementation.

Guide for modifying the Chorus plugin (Claude Code + Codex + OpenClaw ports), updating skill documentation, and releasing new plugin versions.

Complete workflow for submitting code changes — create branch, commit, open PR, check CI, fix failures, and merge.

Release a new version of Chorus — bump version, update CHANGELOG, commit, tag, and create GitHub release.

Optional divergent-then-convergent dialogue for fuzzy ideas. Invoked from the idea skill as a prelude to structured elaboration; produces one ElaborationRound of decision-point Q&A and returns control. Never writes files, never posts comments, never resolves elaboration.

Chorus AI Agent collaboration platform — overview, common tools, setup, and routing to stage-specific skills.

Chorus Development workflow — claim tasks, report work, manage sessions, and integrate with Claude Code Agent Teams.

Chorus Idea workflow — claim ideas, run elaboration rounds, and prepare for proposal creation.

Opt-in OpenSpec-mode authoring for Chorus PM workflows in Claude Code. Detects the local `openspec` CLI, scaffolds `openspec/changes/<slug>/` on disk, and mirrors Markdown files into Chorus document drafts via the `chorus-api.sh` wrapper. Required reading for the proposal, develop, and yolo skills whenever the user has the `openspec` CLI installed.

Adversarial read-only review of a submitted Chorus proposal — document completeness, task granularity, AC↔requirement coverage, and the dependency DAG. Invoke after a proposal is submitted; ends with a VERDICT comment.

Chorus Proposal workflow — create proposals with document and task drafts, manage dependency DAG, validate and submit for review.

Quick Task workflow — skip Idea→Proposal, create tasks directly, execute, and verify.

Chorus Review workflow — approve/reject proposals, verify tasks, and manage project governance.

Adversarial verification of a submitted Chorus task against its AC and proposal documents — read the code, verify each criterion, run tests. Invoke after a task is submitted for verify; ends with a VERDICT comment.

Full-auto AI-DLC pipeline — from prompt to done. Automates the entire Idea -> Proposal -> Execute -> Verify lifecycle.

Read-only Chorus proposal reviewer. Fetches a proposal via MCP, audits PRD/task drafts against the originating Idea, and posts a structured VERDICT comment. Invoke by mounting this skill into a default sub-agent via spawn_agent(agent_type="default", items=[{ type: "skill", path: "chorus:chorus-proposal-reviewer", ... }, { type: "text", text: "Review proposal <uuid>. Max review rounds: 3." }]).

Read-only Chorus task reviewer. Fetches a task plus its acceptance criteria plus originating proposal documents via MCP, independently verifies the implementation, and posts a structured VERDICT comment. Invoke by mounting this skill into a default sub-agent via spawn_agent(agent_type="default", items=[{ type: "skill", path: "chorus:chorus-task-reviewer", ... }, { type: "text", text: "Review task <uuid>. Max review rounds: 3." }]).

Optional divergent-then-convergent dialogue for fuzzy ideas. Invoked from the idea skill as a prelude to structured elaboration; produces one ElaborationRound of decision-point Q&A and returns control. Never writes files, never posts comments, never resolves elaboration.

Chorus Development workflow — claim tasks, report work, self-check acceptance criteria, and submit for verification.

Chorus Idea workflow — claim ideas, run elaboration rounds, and prepare for proposal creation.

Chorus Proposal workflow — create proposals with document and task drafts, manage dependency DAG, validate and submit for review.

Read-only adversarial Chorus proposal reviewer — audits PRD/task drafts against the originating Idea and posts a single structured VERDICT comment.

Quick Task workflow — skip Idea→Proposal, create tasks directly, execute, and verify.

Chorus Review workflow — approve/reject proposals, verify tasks, and manage project governance.

Read-only adversarial Chorus task reviewer — independently verifies an implementation against its acceptance criteria and posts a single structured VERDICT comment.

Full-auto AI-DLC pipeline — drive a single prompt from Idea through Proposal, Execution, and Verification to Done.

Use when manually verifying a Chorus frontend change in a real browser — finding local login credentials, driving the running dev server with the Playwright MCP, logging in, navigating to a page, and capturing snapshots/screenshots for e2e acceptance.

Final ship-time review of an Idea's aggregate code change — the whole feature across all its tasks, not one task. Read the integrated code, check cross-task integration / architecture / security / regression / coverage, run tests. Invoke after the last task of an idea-rooted proposal is verified; ends with a VERDICT comment on the Idea.

Read-only Chorus code-review gateway — the final ship-time review of an Idea''s aggregate code change (the whole feature across all its tasks, not one task). Fetches the Idea, its approved proposals, documents, and tasks via MCP, reviews the aggregate implementation, and posts a structured VERDICT comment on the Idea. Invoke by mounting this skill into a default sub-agent via spawn_agent(agent_type="default", items=[{ type: "skill", path: "chorus:chorus-code-reviewer", ... }, { type: "text", text: "Review the code for idea <uuid>. Round: N." }]).

Read-only adversarial Chorus code-review gateway — independently reviews an Idea's aggregate code change (the whole feature across all its tasks) and posts a single structured VERDICT comment on the Idea.

Guide to audio generation and understanding in MassGen. Covers text-to-speech, music, sound effects, and audio understanding across ElevenLabs and OpenAI backends.

Complete guide for integrating a new LLM backend into MassGen. Use when adding a new provider (e.g., Codex, Mistral, DeepSeek) or when auditing an existing backend for missing integration points. Covers all ~15 files that need touching.

Guide for creating evolving skills - detailed workflow plans that capture what you'll do, what tools you'll create, and learnings from execution. Use this when starting a new task that could benefit from a reusable workflow.

This skill should be used when agents need to search codebases for text patterns or structural code patterns. Provides fast search using ripgrep for text and ast-grep for syntax-aware code search.

Guide to image generation and editing in MassGen. Use when creating images, editing existing images, iterating on image designs, or choosing between image backends (OpenAI, Google Gemini/Imagen, Grok, OpenRouter).

Guide for creating properly structured YAML configuration files for MassGen. This skill should be used when agents need to create new configs for examples, case studies, testing, or demonstrating features.

Guide for using MassGen to develop and improve itself. This skill should be used when agents need to run MassGen experiments programmatically (using automation mode) OR analyze terminal UI/UX quality (using visual evaluation tools). These are mutually exclusive workflows for different improvement goals.

Run MassGen experiments and analyze logs using automation mode, logfire tracing, and SQL queries. Use this skill for performance analysis, debugging agent behavior, evaluating coordination patterns, and improving the logging structure, or whenever an ANALYSIS_REPORT.md is needed in a log directory.

Guide for following MassGen's release documentation workflow. This skill should be used when preparing release documentation, updating changelogs, writing case studies, or maintaining project documentation across releases.

Invoke MassGen's multi-agent system. Use when the user wants multiple AI agents on a task: writing, code, review, planning, specs, research, design, or any task where parallel iteration beats working alone.

Guide for maintaining the MassGen model and backend registry. This skill should be used when adding new models, updating model information (release dates, pricing, context windows), or ensuring the registry stays current with provider releases. Covers both the capabilities registry and the pricing/token manager.

Reference guide for adding new media generation backends to MassGen's unified generate_media tool.

Run comprehensive PR checks including reviewing CodeRabbit comments, ensuring PR description quality, running pre-commit hooks, tests, and validation. Use on an existing PR to address review feedback.

Prepare release documentation including CHANGELOG entry, announcement text, and validation. Run before tagging a new release.

This skill provides semantic search capabilities using embedding-based similarity matching for code and text. Enables meaning-based search beyond keyword matching, with optional document parsing (PDF, DOCX, PPTX) support.

This skill provides symbol-level code understanding and navigation using Language Server Protocol (LSP). Enables IDE-like capabilities for finding symbols, tracking references, and making precise code edits at the symbol level.

Analyze, reorganize, and catalog all installed skills. Merges overlapping skills, restructures the filesystem hierarchy, and generates a compact SKILL_REGISTRY.md routing guide for system prompts.

Develop and debug the MassGen Textual TUI with deterministic replay, snapshot regression tests, and targeted runtime checks.

Guide to video generation in MassGen. Use when creating videos from text prompts or images across Grok, Google Veo, and OpenAI Sora backends.

Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.

Coding principles for simplicity, clarity, and surgical precision. Use when you want Claude to think before coding, keep solutions minimal, make surgical changes, and define verifiable success criteria. Triggers on: karpathy mode, think before coding, simplicity first, surgical changes.

Implements Manus-style file-based planning for complex tasks. Creates task_plan.md, findings.md, and progress.md. Use when starting complex multi-step tasks, research projects, or any task requiring >5 tool calls. Now with automatic session recovery after /clear.

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions

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AI video conversations - create real-time video calls with AI personas

AI-powered web scraping - extract data using natural language prompts

Search Amazon products - find items, compare prices, read reviews

Test and document API endpoints - validate responses, check status, generate examples

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Brand intelligence - logos, colors, fonts, styleguides, and company data from any domain

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Browser automation - control browser sessions, scrape pages, and run AI agents