123 skills · 23 plugins — a self-improving, cross-platform library of reusable AI agent capabilities for Claude Code, GitHub Copilot, Gemini CLI, and any compliant agent framework.
A strictly cross-platform (Windows, Mac, Ubuntu) library — the universal upstream source for reusable AI agent plugins and skills across multiple IDEs and agent frameworks: Claude Code, GitHub Copilot, Gemini CLI, Antigravity, Roo Code, Windsurf, Cursor, and other compliant integrations.
All plugins deploy to the single .agents/ folder standard — no duplicate copies needed for .github, .gemini, .agent, etc.
Important
Start here — fresh clone or first-time setup. The single .agents/ environment directory is not committed to your repo. It will be empty by default.
All installation methods (uvx, bootstrap.py, npx skills, and Marketplace / Extension CLI) are now consolidated in a single authoritative guide:
Quick install (all plugins):
uvx --from git+https://github.com/richfrem/agent-plugins-skills plugin-add richfrem/agent-plugins-skillsThis repository is built on a pragmatic acceptance of the current AI engineering landscape: the ecosystem changes weekly, and workflows that were revolutionary six months ago are obsolete today.
Frameworks like agent-agentic-os and spec-kitty are treated as Transitional Architectures — bridges between what agents need to do today and what native SDKs will eventually handle. When Anthropic, Google, and GitHub harden native memory persistence, execution safety, and multi-agent orchestration, large swaths of this tooling will be happily discarded.
Skills are Applications; the SDK is the OS. Individual skills must function in complete isolation — no hard dependencies on sibling plugins, no assumptions about which framework is running.
The OS implements an eval-gated improvement pipeline for autonomous skill evolution:
os-architect ← intent classifier + ecosystem router
↓
os-improvement-loop ← learning engine: orchestrates multi-iteration improvement
↓
os-eval-runner ← inner gate: KEEP/DISCARD per iteration (evaluate.py)
↓
os-eval-backport ← human gate: review before lab winner → production
↓
os-experiment-log ← scientific backbone: longitudinal tracking + synthesis
Entry point: /os-architect — describe what you want in plain language. The agent classifies intent, audits the ecosystem, proposes Path A/B/C, and dispatches via your available CLI tools. os-evolution-planner writes the task plan + delegation prompt. os-architect-tester validates after any changes.
Skills that score HIGH on the autoresearch viability rubric (objectivity + speed + frequency + utility) can run fully autonomous self-improvement loops:
mutate SKILL.md → evaluate.py → exit 0 (KEEP) or exit 1 (DISCARD) → repeat
Not all skills are good candidates — use eval-autoresearch-fit to score a skill before running a loop.
Live example — convert-mermaid skill, 26 iterations across 2 rounds: 0.61 → 1.00
Each blue diamond is a baseline anchor (one per session). Green = new best score. Amber = kept but not a record. The two-segment shape shows a fresh re-baseline for round 2.
Monitor a live run: python plugins/agent-agentic-os/scripts/plot_eval_progress.py --tsv <lab>/evals/ --live
Flywheel layers:
- OUTER flywheel (
os-improvement-loop): improves OS-level protocols and session ledgers between sessions - INNER flywheel (
os-eval-runner): evaluate.py KEEP/DISCARD gate per iteration within a session
5 composable primitives used as the execution substrate by the Improvement OS and standalone by any agent workflow:
learning-loop · dual-loop · agent-swarm · red-team-review · triple-loop-learning
O(1) RLM keyword → O(log N) vector semantic → wiki concept nodes.
Super-RAG stack: rlm-factory (O(1) keyword) + vector-db (O(log N) semantic) + obsidian-wiki-engine (full concept nodes)
Each plugin works standalone (Mode A) or combined for full Super-RAG power. Init agents detect what is installed in .agents/skills/ and configure only the available layers.
All shared scripts live once at plugins/<plugin>/scripts/. Skills reference them via file-level symlinks (skills/<skill>/scripts/script.py → ../../../scripts/script.py). Directory-level symlinks are forbidden — npx drops them on install.
The flagship operational framework. Eval-gated improvement loops, memory management, session lifecycle, and ecosystem evolution orchestration.
Skills (16): os-architect · os-evolution-planner · os-guide · os-improvement-loop · os-eval-lab-setup · os-eval-runner · os-eval-backport · os-environment-probe · os-evolution-verifier · os-experiment-log · os-memory-manager · os-improvement-report · os-init · os-clean-locks · todo-check · optimize-agent-instructions
Agents: os-architect-agent · os-architect-tester-agent · improvement-intake-agent · os-health-check · agentic-os-setup
Enterprise-grade Spec → Plan → Tasks → Implement → Review → Merge pipeline.
Skills (19): spec-kitty-specify · spec-kitty-plan · spec-kitty-tasks · spec-kitty-implement · spec-kitty-review · spec-kitty-merge · spec-kitty-analyze · spec-kitty-accept · spec-kitty-clarify · spec-kitty-research · spec-kitty-dashboard · spec-kitty-status · spec-kitty-checklist · spec-kitty-constitution · spec-kitty-tasks-outline · spec-kitty-tasks-finalize · spec-kitty-tasks-packages · spec-kitty-workflow · spec-kitty-sync-plugin
Agents: spec-kitty-agent · spec-kitty-setup
Autonomous discovery loop: idea framing → business requirements → user stories → prototype → handoff into formal engineering specs.
Skills (11): exploration-workflow · exploration-session-brief · discovery-planning · business-requirements-capture · business-workflow-doc · user-story-capture · exploration-handoff · exploration-optimizer · prototype-builder · visual-companion · subagent-driven-prototyping
Agents (11): business-rule-audit-agent · discovery-planning-agent · exploration-cycle-orchestrator-agent · handoff-preparer-agent · intake-agent · planning-doc-agent · problem-framing-agent · prototype-builder-agent · prototype-companion-agent · requirements-doc-agent · requirements-scribe-agent
5 execution primitives used as the substrate for the Improvement OS and standalone agent workflows.
Skills (6): orchestrator · learning-loop · dual-loop · agent-swarm · red-team-review · triple-loop-learning
Agents: orchestrator
Centralized rules engine for file headers, naming conventions, and linting across Python, TypeScript, and C#.
Skills (1): coding-conventions-agent · Agent: coding-conventions-agent
Interactive creators for exact file hierarchies + structured audit framework for plugin architectural maturity.
Scaffolding skills: create-plugin · create-skill · create-sub-agent · create-command · create-hook · create-github-action · create-agentic-workflow · create-azure-agent · create-docker-skill · create-mcp-integration · create-stateful-skill
Audit & analysis skills: audit-plugin · audit-plugin-l5 · l5-red-team-auditor · analyze-plugin · self-audit · mine-skill · mine-plugins · path-reference-auditor · fix-plugin-paths · synthesize-learnings · eval-autoresearch-fit · manage-marketplace · ecosystem-standards · ecosystem-authoritative-sources
Continuous markdown hyperlink validation with multi-stage pipeline (inventory → extract → audit → fix).
Skills (2): link-checker-agent · symlink-manager · Agent: link-checker-agent
Dispatch specialized analysis to isolated fresh model contexts via CLI tools (security audits, architecture review, QA).
Skills (3): claude-cli-agent · claude-project-setup · optimize-context
Agents (3): architect-review · refactor-expert · security-auditor
Skills (1): copilot-cli-agent — GPT-5 mini via Copilot CLI; used in autoresearch mutation delegation
Agents (3): architect-review · refactor-expert · security-auditor
Skills (2): gemini-cli-agent · antigravity-project-setup
Agents (3): architect-review · refactor-expert · security-auditor
Behavioural guardrails enforcing best practices on every coding session. These skills come from obra/superpowers — install that plugin to get them. This ecosystem builds on superpowers rather than duplicating it.
Install: uvx --from git+https://github.com/richfrem/agent-plugins-skills plugin-add obra/superpowers
Skills available via superpowers: verification-before-completion · test-driven-development · using-git-worktrees · systematic-debugging · finishing-a-development-branch · requesting-code-review
Karpathy-style LLM wiki with cross-source concept synthesis. Transforms raw markdown sources into structured, queryable concept nodes. Full Obsidian vault CRUD, canvas, and graph traversal.
Wiki skills: obsidian-wiki-builder · obsidian-rlm-distiller · obsidian-query-agent · obsidian-wiki-linter
Vault skills: obsidian-init · obsidian-vault-crud · obsidian-canvas-architect · obsidian-graph-traversal · obsidian-markdown-mastery · obsidian-bases-manager
Setup agents: wiki-init-agent · wiki-build-agent · wiki-distill-agent · wiki-lint-agent · wiki-query-agent · super-rag-setup-agent
Dense per-file summaries with zero external dependencies. Works standalone or as Phase 1 of the Super-RAG stack.
Skills (6): rlm-init · rlm-curator · rlm-search · rlm-distill-agent · rlm-cleanup-agent · rlm-audit
Setup agent: rlm-factory-init-agent (guided setup, Modes A–D)
ChromaDB-driven semantic embedding indexing with Parent-Child retrieval. Supports In-Process mode (zero server setup) and HTTP Server mode. Works standalone or as Phase 2 of the Super-RAG stack.
Skills (6): vector-db-init · vector-db-launch · vector-db-ingest · vector-db-search · vector-db-cleanup · vector-db-audit
Setup agent: vector-db-init-agent — guided wizard (Modes A–D)
Multi-tiered cognition and context caching between long-term persistent storage and active memory.
Skills (1): memory-management
Skills (3): plugin-installer · plugin-remover · plugin-syncer
Skills (1): task-agent
Cross-platform pip-compile with strict .in → .txt lockfile discipline.
Skills (1): dependency-management
Package deep directory contexts and code traces into single payloads for external LLM review.
Skills (2): context-bundler · red-team-bundler
Skills (1): convert-mermaid (autoresearch score: 30/40 MEDIUM — eval run complete: 0.61 → 1.00 in 26 iterations)
Skills (1): adr-management
Skills (2): hf-init · hf-upload
Skills (1): humanize
Token-stream speed reading with pause/resume, comprehension check-ins, and session management.
Skills (2): rsvp-reading · rsvp-comprehension-agent
Scored all 116/120 production skills for Karpathy autoresearch loop viability using GPT-5 mini via Copilot CLI. Each skill scored on: objectivity (can a shell command measure it?), execution speed, frequency of use, and potential utility (max 40).
Top HIGH candidates:
| Rank | Skill | Score | Loop |
|---|---|---|---|
| 1 | superpowers/verification-before-completion | 35/40 | LLM_IN_LOOP |
| 2 | superpowers/test-driven-development | 35/40 | LLM_IN_LOOP |
| 3 | coding-conventions/coding-conventions-agent | 34/40 | HYBRID |
| 4 | superpowers/using-git-worktrees | 33/40 | DETERMINISTIC |
| 5 | spec-kitty-plugin/spec-kitty-status | 33/40 | DETERMINISTIC |
| 6 | agent-agentic-os/os-eval-runner | 32/40 | DETERMINISTIC |
Full ranked results: summary-ranked-skills.json
Top 20 opportunities with metrics + blockers: autoresearch-opportunities-report.md
Regenerate report:
python plugin-research/experiments/analyze-candidates-for-auto-reseaarch/skills/eval-autoresearch-fit/scripts/update_ranked_skills.py \
--json-path plugin-research/experiments/analyze-candidates-for-auto-reseaarch/skills/eval-autoresearch-fit/assets/resources/summary-ranked-skills.json \
--morning-reportplugins/ ← upstream source (23 plugins, 123 skills)
<plugin>/
plugin.json
skills/<skill>/
SKILL.md ← skill definition (mutation target for autoresearch loops)
evals/evals.json ← routing evaluation suite (should_trigger boolean schema)
evals/results.tsv ← per-experiment score history
autoresearch/ ← optional: evaluate.py + golden task set for improvement loops
scripts/ ← file-level symlinks → ../../scripts/
scripts/ ← canonical scripts (shared via symlinks, never duplicated)
agents/ ← sub-agent .md definitions
assets/diagrams/ ← architecture diagrams
.agents/ ← deployed skill copies (bridge installer output)
skills/
agents/
plugin-research/ ← experiments and autoresearch infrastructure
experiments/
analyze-candidates-for-auto-reseaarch/
temp/ ← local scratch (gitignored except scripts)
ecosystem-fitness-sweep-v1/
123 skills · 23 plugins · Improvement OS (os-architect) · Karpathy autoresearch loops · Super-RAG 3-tier retrieval