Reusable expertise for your agents
Read the complete instructions before you install. Every listing keeps its source, license, repository context, and pinned commit visible.
Curated directory
Featured Agent Skills
Ranked by source completeness, transparent community-adoption estimates, real Skill-level Dokki installs, and repository diversity.
- agent-tooling
memory-engineering
Use when designing, reviewing, or paying for an agent memory system — adding memory to an agent, choosing between long-context / RAG / graph / agentic memory, auditing what a CLAUDE.md or memory directory actually holds, deciding what to keep and what to expire, or when a memory store keeps growing and nobody has said what leaves it. Prices the write path, picks which cost to pay, classifies records as facts / skills / logs, and refuses a design that has no forgetting policy.
3k est. installs25k stars - agent-tooling
memory-review
Analyze auto-memory for promotion candidates, stale entries, consolidation opportunities, and health metrics. Use when the user runs /si:memory-review or asks what has been learned and what should be promoted or pruned.
3k est. installs25k stars - agent-tooling
memory-status
Memory health dashboard showing line counts, topic files, capacity, stale entries, and recommendations. Use when the user runs /si:memory-status or asks how full or healthy the agent memory is.
3k est. installs25k stars - agent-tooling
merge
Merge the winning agent's branch into base, archive losers, and clean up worktrees. Use when the user runs /hub:merge or asks to land the winning AgentHub result and tidy the session.
3k est. installs25k stars - agent-tooling
promote
Graduate a proven pattern from auto-memory (MEMORY.md) to CLAUDE.md or .claude/rules/ for permanent enforcement. Use when the user runs /si:promote or asks to make a learned behavior permanent.
3k est. installs25k stars - agent-tooling
prompt-governance
Use when managing prompts in production at scale: versioning prompts, running A/B tests on prompts, building prompt registries, preventing prompt regressions, or creating eval pipelines for production AI features. Triggers: 'manage prompts in production', 'prompt versioning', 'prompt regression', 'prompt A/B test', 'prompt registry', 'eval pipeline'. NOT for writing or improving individual prompts (use senior-prompt-engineer). NOT for RAG pipeline design (use rag-architect). NOT for LLM cost reduction (use llm-cost-optimizer).
3k est. installs25k stars - agent-tooling
remember
Explicitly save important knowledge to auto-memory with timestamp and context. Use when a discovery is too important to rely on auto-capture.
3k est. installs25k stars - agent-tooling
run
One-shot lifecycle command that chains init → baseline → spawn → eval → merge in a single invocation. Use when the user runs /hub:run or asks to execute a full AgentHub competition end-to-end.
3k est. installs25k stars - agent-tooling
run
Run a single experiment iteration. Edit the target file, evaluate, keep or discard. Use when the user runs /ar:run or asks for one manual autoresearch iteration.
3k est. installs25k stars - agent-tooling
run-without-you
Phase 4 of building a Claude Managed Agent — make it run without you. Turn a graded agent into a recurring scheduled deployment (POSIX-cron), an event-driven curl trigger, or confirmed on-demand use, then finalize the versioned roadmap. Use when the user says "run it every morning", "put it on a schedule", "nightly", "weekly", "automate this", "make it recurring", or when the orchestrator routes phase=run-without-you. deployment_builder.py builds the POST /v1/deployments payload (initial_events must include user.message; optionally nests a user.define_outcome so each firing self-grades); cron_validator.py validates the 5-field cron + IANA timezone and prints the wall-clock DST note; next_directions_writer.py writes NEXT-DIRECTIONS.md. No tool makes API calls — the deployment is created via BYOK curl. Distinct from grade-iterate (the in-session loop) and wrap-up (closeout).
3k est. installs25k stars - agent-tooling
self-improving-agent
Curate Claude Code's auto-memory into durable project knowledge. Analyze MEMORY.md for patterns, promote proven learnings to CLAUDE.md and .claude/rules/, extract recurring solutions into reusable skills. Use when: (1) reviewing what Claude has learned about your project, (2) graduating a pattern from notes to enforced rules, (3) turning a debugging solution into a skill, (4) checking memory health and capacity.
3k est. installs25k stars - agent-tooling
senior-prompt-engineer
Use when the user asks to optimize prompts, design prompt templates, evaluate LLM outputs with an eval set, measure RAG retrieval quality, validate agent/tool configurations, analyze token usage, or design structured-output contracts. Covers eval-driven prompt iteration, RAG metrics (relevance, faithfulness, coverage), agent workflow validation, and token/cost budgeting — all model-agnostic, with three stdlib Python tools.
3k est. installs25k stars - agent-tooling
setup
Set up a new autoresearch experiment interactively. Collects domain, target file, eval command, metric, direction, and evaluator. Use when the user runs /ar:setup or asks to start optimizing a file with the autoresearch loop.
3k est. installs25k stars - agent-tooling
skill-doctor
Use when the user wants their agent setup graded from real conversation history, asks which installed skills are actually working, or wants evidence-backed skill edits — scores recent local Claude Code / Codex sessions against efficiency and code-quality rubrics, then drafts skill changes gated by a deterministic aggregator and renders one local shareable report.
3k est. installs25k stars - agent-tooling
skill-tester
Validate, test, and score the quality of skills within the claude-skills ecosystem. Comprehensive meta-skill: structure validation, Python script testing (syntax + imports + runtime + output format), multi-dimensional quality scoring with letter grades and tier classification (BASIC/STANDARD/POWERFUL). Use when authoring a new skill, auditing existing skills for tier promotion, setting up pre-commit hooks for skill quality, or integrating skill QA into CI.
3k est. installs25k stars - agent-tooling
skillopt-sleep
Use when the user wants their Claude agent to self-improve from past usage, asks about a nightly/offline 'sleep' or 'dream' cycle, memory/skill consolidation, or says things like 'make my agent better the more I use it', 'review my past sessions', 'learn my preferences', 'consolidate what you learned', 'run the sleep cycle', or wants to schedule offline self-optimization. Drives the skillopt_sleep engine: harvest past sessions -> mine recurring tasks -> replay offline -> consolidate validated CLAUDE.md and SKILL.md behind a held-out gate.
3k est. installs25k stars - agent-tooling
spawn
Launch N parallel subagents in isolated git worktrees to compete on the session task. Use when the user runs /hub:spawn or asks to start the competing agents for an initialized AgentHub session.
3k est. installs25k stars - agent-tooling
spec-driven-workflow
Use when the user asks to write specs before code, define acceptance criteria, plan features before implementation, generate tests from specifications, or follow spec-first development practices.
3k est. installs25k stars