Claude Skills
The open format is called Agent Skills and works in Claude Code, Codex, Cursor and other agents — most people know it as Claude Skills.
Every Agent Skill we could find on GitHub, deduplicated by content. 79 437 files from 1 744 authors, of which 61 785 are unique — the rest is the same skill repackaged into someone else's repository. For each one: what it weighs in tokens, whether it ships runnable scripts, and which MCP servers it needs.
Install and configure the GitHub CLI (gh) for AI agent environments where gh may not be pre-installed and git remotes use local proxies instead of github.com. Use when gh command not found, shutil.which returns None, need GitHub API access for issues or PRs or releases or workflow runs, or repository operations fail with 'failed to determine base repo' error. Provides auto-install script with SHA256 verification, GITHUB_TOKEN auth with anonymous fallback, and the required -R flag pattern for proxy environments. Covers project management via GitHub Projects V2, milestones via REST API, issue lifecycle templates, and label taxonomy management.
Analyze git repository history to produce a codebase risk profile before code review. Probes repo size, runs 7 parallel git analysis pipelines (hotspots, bug magnets, bus factor, contributor momentum, firefighting frequency, newly added files), cross-references hotspots with bug magnets to identify high-risk files with primary owner annotation, and writes walkthrough/recon-report.md. Use before code review to prioritize reviewer attention, at the start of linear-walkthrough Phase 1 Discovery to weight file coverage, or when onboarding to an unfamiliar codebase.
Assign backlog items to a GitHub milestone by bridging per-item files to GitHub Issues. Use when populating a sprint or release milestone, after create-milestone, or when a milestone number is specified with optional P0/P1/P2 or title filter. Creates missing GitHub Issues for selected P0/P1 items, assigns all selected items to the milestone, and updates Project V2 Status to Backlog.
Manages the research/ knowledge base of verified tool and library research entries via knowledge-explorer.py. Commands — list (browse by category or SDLC layer), fetch-github (draft entry from GitHub repo), add (validate and route to category dir), update-append (append dated revision), generate-descriptions (repair missing or low-quality descriptions), migrate (convert inline-header entries to frontmatter). Use when browsing KB topics, adding or updating research entries, fetching GitHub repo metadata, generating descriptions in parallel via Haiku subagents, or migrating old-format entries to skill-spec frontmatter.
Produces a structured, end-to-end linear walkthrough of an unfamiliar codebase by orchestrating parallel subagents across four phases — discovery, tracing, validation, and synthesis. Use when onboarding to a new repository, understanding execution paths from entry points, generating navigable codebase documentation, or needing fact-checked coverage of architecture, deployment, testing, and operations.
Modern Git workflows, best practices, and commands. Use when the user asks about Git branch management (git switch vs checkout), file restoration (git restore), fixup commits, autosquash rebasing, git worktrees, rerere, force-with-lease, repository cleanup (git clean, stale branches, bloat analysis), history navigation (revision syntax, range notation, pickaxe search), recommended global git config, or GitButler and the but CLI.
Facade skill for multi-agent swarm orchestration in Claude Code — routes to specialist skills covering primitives, spawning, operations, and patterns. Use when coordinating multiple agents in parallel, building pipeline workflows with dependencies, running parallel code reviews, creating self-organizing task queues, designing divide-and-conquer workloads, or choosing between TeamCreate and Agent tool approaches. Loads swarm-primitives (team lifecycle and message flow), swarm-spawning (agent types and backends), swarm-operations (tool API and error handling), and swarm-patterns (six orchestration recipes with complete workflows).
Transforms validated /linear-walkthrough artifacts into one presentation-ready deck outline per major codebase component. Use when the user asks to create a presentation, prepare a walkthrough deck, build an onboarding deck, produce an architecture review deck, or summarize a codebase for a technical audience. Requires walkthrough directory output -- reads unified walkthrough, per-section files, validation reports, coverage maps, entry points, and open questions -- then orchestrates four parallel agent phases to produce slide outlines with speaker notes, evidence references, and suggested visuals.
Badge design and selection knowledge base for shields.io badges in README files. Use when writing or updating READMEs, choosing badge layouts, selecting badge styles, adding project health indicators, or picking Simple Icons logo slugs. Covers shields.io URL encoding rules, static vs dynamic badge selection, style variants (flat/flat-square/for-the-badge/social/plastic), layout patterns (two-tier/inline/centered), project-type badge sets for Python/JS/Rust/Claude plugins, color reference, non-obvious logo slugs, and common anti-patterns to avoid.
Strategic rebase with mandatory pre-analysis. Use when asked to rebase a branch onto main (or any target). Runs a file-level diff of both sides before touching git, produces a per-file disposition plan (KEEP/MERGE/DROP/REWRITE), and only then executes the rebase. Prevents surprise conflicts and silent data loss from rebasing without knowing what changed on both sides. Triggers: 'rebase', 'rebase onto main', 'rebase this branch', 'rebase and merge', 'update branch from main'.
Bulk-refresh research entries in ./research/ using parallel research-curator agents. Use when /refresh-research is invoked, stale research needs updating, or bulk re-verification of research entries is requested. Inventories entries by review date and age, runs RT-ICA pre-flight, spawns agents in waves of 5, updates README and Freshness Tracking, lints and commits. Supports --all, --stale, --category, --layer, and --dry-run flags.
Orchestrate research entry lifecycle in ./research/ — create, batch-import, refresh stale entries, and validate structure. Use when asked to add a tool, research a URL, document a library, refresh research, validate entries, or given any tool or library URL. Supports --batch (parallel multi-URL), --rerun (refresh one or all entries), and --validate (structural check with auto-fix of error-severity issues).
Look up prior Claude Code sessions when context is lost or forgotten. Use when asked what was done before, what happened in the last session, or any request to recall past conversation history, prior decisions, experiments, or outcomes. Indexes and searches raw JSONL transcripts from ~/.claude/projects/ via DuckDB. Returns verbatim user messages, summarizes AI actions and sub-agent outcomes, detects tool errors and user frustration signals, and reports tool usage statistics. Summaries cached at ~/.claude/kaizen/session-summaries/.
Walks a user from one rough content idea to a finished post, platform-adapted variants, and repurposed follow-on assets using a 7-step sequential prompting workflow. Use when the user wants to turn a half-formed idea, frustration, story, or client situation into publishable content quickly and consistently — covering idea extraction, hook generation, outline, draft, humanizer pass, platform adaptation (LinkedIn, Reddit, X/Twitter, newsletter, Telegram), and repurpose engine.
Builds comprehensive Claude Code skills using parallel research agents — categorization, parallel documentation gathering, anti-hallucination checkpoints, and final validation. Use when building a skill from official docs, when "research for skill" or "create comprehensive skill" is requested, or when extensive multi-source documentation gathering is needed before skill creation.
Transitions a GitHub milestone from planning to active execution. Use when the team is ready to begin a sprint or release cycle — bulk-transitions open issue labels from status:needs-grooming to status:in-progress, updates GitHub Projects V2 Status to In Progress, and confirms before applying changes. Requires milestone number as argument. Use after /group-items-to-milestone.
Parse a markdown file's unchecked checkbox items (- [ ]) and generate a self-organizing Claude Code swarm task pool. Use when you have a todo.md, checklist.md, or any markdown file with checkbox items and want to dispatch them as parallel swarm tasks using TeamCreate + TaskCreate + worker agents. Skips checked items (- [x] / - [X]) automatically.
API reference for Claude Code multi-agent swarm tools -- TeamCreate, SendMessage, TeamDelete, TaskCreate/Update/List/Get, and Agent tool parameters. Use when looking up tool signatures, message schemas, shutdown sequences, error handling patterns, or debugging swarm operations. Covers direct messages, broadcasts, plan approval flows, graceful shutdown sequences, crashed teammate recovery, and common error causes.
Recipes and patterns for Claude Code multi-agent swarms. Use when building parallel specialist reviews, pipeline workflows, self-organizing swarms, research-then-implement flows, plan approval gates, coordinated multi-file refactoring, or any divide-and-conquer orchestration pattern requiring TeamCreate, TaskCreate, SendMessage, or Agent tool coordination.
Conceptual foundation for Claude Code multi-agent orchestration -- defines teams, teammates, leaders, tasks, inboxes, messages, and backends and shows how they connect. Use when starting to build a swarm workflow, understanding the swarm lifecycle and file layout, reading team config structure, or learning the task dependency system before writing TeamCreate or Agent tool calls.
Covers how to create agents in Claude Code swarms -- subagents vs teammates, built-in agent type catalog (Bash, Explore, Plan, general-purpose, claude-code-guide), plugin agent types from compound-engineering, spawn backend selection (in-process, tmux, iterm2) with auto-detection logic, and environment variables injected into spawned agents. Use when choosing how to spawn an agent, selecting the right agent type, configuring or troubleshooting spawn backends, or passing env vars to teammates.
Creative reasoning framework for ill-defined problems where conventional solutions are suboptimal. Use when the problem has ambiguous goals, vast solution space, no single correct answer, or requires innovation. Implements three paradigms — combinational (novel combinations of familiar ideas), exploratory (expand solution space boundaries), transformative (alter fundamental constraints). Do not use for well-defined problems, mathematical puzzles, or tasks requiring convergent reasoning.
Scientific delegation framework for orchestrators coordinating sub-agents. Provides WHERE-WHAT-WHY context patterns while preserving agent autonomy. Use when delegating tasks, structuring sub-agent prompts, planning multi-agent workflows, or coordinating specialist agents.
Quick delegation template for sub-agent prompts. Use when assigning work to a sub-agent, before invoking the Agent tool, or when preparing prompts for specialized agents. Provides the WHERE-WHAT-WHY framework. For comprehensive delegation guidance, activate the agent-orchestration how-to-delegate skill.
Scientific delegation framework for orchestrators — provide observations and success criteria while preserving agent autonomy. Use when assigning work to sub-agents, before invoking the Agent tool, or when preparing delegation prompts for specialist agents.
Master multi-agent orchestration using Claude Code's swarm system. Use when coordinating multiple agents, running parallel code reviews, creating pipeline workflows with dependencies, building self-organizing task queues, or any task benefiting from divide-and-conquer patterns. This facade loads specialist skills for primitives, spawning, operations, and patterns.
Agentskill kaizen plugin documentation index. Load when needing to read about cross-platform notes, improvement plans, or DuckDB integration.
Transform transcript analysis findings into actionable improvements. Triggers on "generate hooks from findings", "improve agent", "fix anti-pattern", "kaizen improvement", "generate hook proposals", or "create improvement plan". Provides templates for hook generation, agent prompt refinement, skill patches, CLAUDE.md updates, and script automation from analysis data.
Use when extracting specific data points from large agent output transcripts, kaizen analysis reports, or JSONL session files — tool timings, query counts, error summaries, or any structured facts — without loading raw data into orchestrator context. Activates when the orchestrator needs targeted facts from large files and context pollution must be avoided.
This skill should be used when analyzing Claude Code session transcripts, reviewing agent performance, finding anti-patterns or tool misuse, detecting user frustration signals, mining workflow patterns, running kaizen analysis, debugging agent behavior, or performing session forensics. Provides JSONL schema (kaizen-analysis get_transcript_jsonl_schema or MCP resource kaizen://session-log/schema or references/jsonl-schema.md), arbitrary DuckDB SQL over JSONL via kaizen-duckdb execute_query, cookbook query patterns, 10 analysis dimensions, and PM4Py process mining methodology.
Bash 5.1 release features and improvements with practical examples. Use when working with Bash 5.1 features, epoch time variables, redirection enhancements, or when user asks about Bash 5.1 changes, new features, or version-specific capabilities.
Bash 5.2 release features and improvements with practical examples. Use when working with Bash 5.2 features, variable handling enhancements, readline improvements, or when user asks about Bash 5.2 changes, new features, or version-specific capabilities.
Bash 5.3 release features and improvements with practical examples. Use when working with Bash 5.3 features, new command substitution, GLOBSORT, loadable builtins, or when user asks about Bash 5.3 changes, new features, or version-specific capabilities.
This skill should be used when the user asks to "write a bash script", "create a shell script", "implement bash function", "parse arguments in bash", "handle errors in bash", or mentions bash development, shell scripting, script templates, or modern bash patterns.
This skill should be used when the user asks to "lint bash script", "run shellcheck", "format shell script", "use shfmt", "fix shellcheck errors", or mentions shell script linting, formatting, code quality, or pre-commit hooks for bash.
This skill should be used when the user asks to "add logging to bash script", "colorize output", "implement log levels", "CI/CD sections", "terminal colors in bash", or mentions logging functions, emoji output, collapsible CI sections, or shlocksmith.
This skill should be used when the user asks about "POSIX compatibility", "portable shell scripts", "cross-shell compatibility", "bashisms", "shebang selection", or mentions writing scripts that work on different shells (bash, sh, dash, zsh) or different systems.
This skill should be used when the user asks to "test bash script", "write shell tests", "use shunit2", "use shellspec", "create test suite for bash", or mentions unit testing, test frameworks, mocking, or test-driven development for shell scripts.
You MUST use this before any creative work - creating features, building components, adding functionality, modifying behavior, or when users request help with ideation, marketing, and strategic planning. Explores user intent, requirements, and design before implementation using 30+ research-validated prompt patterns.
Configure clang-format code formatting. Use when: user mentions clang-format or .clang-format, analyzing code style/patterns, creating/modifying formatting config, troubleshooting formatting, brace styles/indentation/spacing/alignment/pointer alignment, or codifying conventions.
When setting up commit message validation for a project. When project has commitlint.config.js or .commitlintrc files. When configuring CI/CD to enforce commit format. When extracting commit rules for LLM prompt generation. When debugging commit message rejection errors.
When writing a git commit message. When task completes and changes need committing. When project uses semantic-release, commitizen, git-cliff. When choosing between feat/fix/chore/docs types. When indicating breaking changes. When generating changelogs from commit history.
Use when querying, modifying, or converting JSON, YAML, TOML, XML, CSV, HCL, or INI with dasel v3. Complete reference for selectors, functions, conditionals, variables, spread operator, type casting, and format-specific patterns.
Use when exploring unknown structured data files with dasel v3 — discover schema, list keys, find nested values, sample arrays, identify data types across JSON, YAML, TOML, XML, CSV, HCL, INI formats
Use when modifying, converting, or transforming structured data with dasel v3 — in-place mutations, format conversion, batch operations, array manipulation, object construction, and merge patterns across JSON, YAML, TOML, XML, CSV, HCL, INI
Dasel v3 query patterns for Hibernate .hbm.xml mapping files — entity-table binding, Java property-to-column extraction, one-to-many set/list/bag relationship tracing, many-to-one foreign key discovery, batch scanning across 60+ HBM files. Use when querying Hibernate ORM class mappings, extracting schema metadata from Java persistence layer, or auditing entity-column relationships in enterprise legacy codebases.
Dasel v3 query patterns for InstallAnywhere .iap_xml installer definitions — use when querying action sequences, discovering variables, resolving platform conditions, navigating panels, or comparing installer variants. Files are 2.5+ MB, 65,000+ lines — too large for context reads, requires structural dasel queries.
Dasel v3 selector patterns for Maven POM XML files — use when querying dependency versions, filtering by groupId or scope, extracting module hierarchy from parent POMs, or detecting version conflicts across enterprise multi-module Java projects. Load this skill when working with pom.xml files using dasel.
Dasel v3 selectors for Spring bean factory XML — use when querying any Spring ApplicationContext XML for bean discovery, dependency wiring, JMS destination mapping, property injection extraction, or cross-bean reference tracing. Load this skill before writing dasel selectors against Spring bean XML files (applicationContext.xml, *_beans.xml, spring-*.xml).
Dasel v3 patterns for querying Tomcat web.xml deployment descriptors — use when inspecting servlet enumeration, filter chain discovery, listener listing, context parameter extraction, or init-param inspection in web.xml files
Use when installing, updating, or troubleshooting the dasel v3 binary — runs the install script, verifies installation, and diagnoses PATH and download issues
SAM-style feature initiation workflow — discovery through codebase analysis, architecture spec, task decomposition, validation, and context manifest. Use when a user asks to add a feature, plan a feature, or convert an idea into executable task files.
Use when analyzing failing test cases to determine whether failures indicate genuine bugs or test implementation issues. Activates on "analyze failing tests", "debug test failures", "investigate test errors", or when provided with specific failing test names or output. Applies balanced investigative reasoning — does not auto-fix tests without establishing root cause.
Fetch and report current API syntax, changelog entries, and breaking changes for a specific library or protocol version. One research angle within a parallel technical-research set — runs independently and returns a structured cited report. Invoke when a specific library name and version are the target.
Administer the backlog tooling ecosystem when a capability gap is discovered. Invoke when backlog.py, backlog skills, or backlog agents lack a needed operation and a workaround was used or is about to be used. Classifies gaps as script (delegates to @python-cli-architect), process (loads improve-processes), or documentation (delegates to @ai-doc-optimizer). Domain: backlog.py, create/work/groom-backlog-item skills, backlog-item-groomer agent, hooks, templates, references, rules, and tests.
Use when creating, listing, viewing, updating, closing, resolving, grooming, or syncing backlog items and GitHub Issues — single interface for all backlog CRUD via MCP tools (mcp__plugin_dh_backlog__*). GitHub Issues are the source of truth; direct file edits are bypassed in favour of MCP tool calls.
Use when orchestration or planning agents are producing task plans, task prompts, or TASK.md instructions that must be unambiguous, verifiable, and resistant to hallucination. Applies CLEAR (Concise, Logical, Explicit, Adaptive, Reflective) to structure and write agent task files, then adds CoVe (Chain of Verification) checks where accuracy risk is meaningful. Activates on draft task prompts, swarm plans, migration tasks, and multi-step plans requiring independently executable steps.
Use when a task asks for architecture review, dependency graph visualization, module coupling analysis, or circular dependency detection. Auto-detects scope (git diff → PR diff → full project). Reads project config (pyproject.toml, tsconfig.json, go.mod, Cargo.toml) to establish the intra-project module namespace before parsing imports. Builds a module-dependency graph across Python, TypeScript, JavaScript, Go, Rust, and Java. Detects cycles via graphify output or an executable Python script. Checks Conway's Law alignment against CODEOWNERS and directory structure. For Claude plugin repos, also traces cross-language chains: hook configs → hook scripts, SKILL.md/agent docs → node/uv-run scripts, PEP 723 inline deps, and MCP tool calls. Emits Mermaid flowcharts with severity color-coding (red = circular dep, yellow = high-coupling, green = clean, blue = Conway violation). Applies recursive semantic partitioning for graphs > 40 nodes. Registers each diagram as a codebase-analysis artifact.
Loaded automatically when reviewing Claude skills or agent definitions — covers SKILL.md structure, frontmatter validity, token budget, description quality, and agent contract compliance.
Reviews CLI application code for correctness and quality. Use when reviewing tools that use argparse, click, typer, commander.js, or similar argument parsers — covers exit codes, help flags, stdin/stdout/stderr separation, non-interactive operation, signal handling, argument validation, ANSI color safety, and dry-run support for destructive operations.
Claude Skills — questions
Answers built from the skills we actually parsed.