--- license: mit pretty_name: ctx tags: - agents - mcp - skills - knowledge-graph - llm-wiki - recommendation-system - harness - codex - claude-code --- # ctx — Skill, Agent, MCP & Harness Recommendations [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](LICENSE) [![Python 3.11+](https://img.shields.io/badge/Python-3.11+-green.svg)](https://python.org) [![PyPI](https://img.shields.io/pypi/v/claude-ctx.svg)](https://pypi.org/project/claude-ctx/) [![Tests](https://img.shields.io/badge/Tests-3831_collected-brightgreen.svg)](#) [![Graph](https://img.shields.io/badge/Graph-102%2C720_nodes_/_2.9M_edges-red.svg)](graph/) [![Docs](https://img.shields.io/badge/docs-MkDocs_Material-blue.svg)](https://stevesolun.github.io/ctx/) [![Repo views](https://hits.sh/github.com/stevesolun/ctx.svg?label=repo%20views)](https://hits.sh/github.com/stevesolun/ctx/) ctx watches what you are building, walks a **102,720-node** graph, and recommends a small, top-scored bundle of skills, agents, and MCP servers for the current task. If you use your own local/API model instead of Claude Code, ctx has a separate harness setup flow: tell it the model and goal, review the recommended harness, then install with dry-run/update/uninstall controls. Current shipped snapshot: - **91,450 skills** with hydrated installable `SKILL.md` bodies. - **467 agents**, **10,787 MCP servers**, and **16 harnesses**. - **2.9M graph edges** across semantic similarity, tags, slug tokens, source overlap, direct links, quality, usage, type affinity, and graph structure. - **89,465 hydrated `SKILL.md` bodies** in the shipped LLM-wiki; long entries are converted through the micro-skill gate instead of loading raw long prompts. - Entity updates for skills, agents, MCPs, and harnesses print benefits/risks and skip replacement unless you explicitly approve the update. ## Why it exists - **Discovery** — with 91K+ skill nodes, 460+ agents, 10K+ MCP servers, and 16 harnesses, you can't possibly know which exist or which apply to your current work. - **Context budget** — loading everything wastes tokens and degrades quality. You need the right 10–15 per session. - **Skill rot** — skills you installed months ago and never used are cluttering context. Stale ones should be flagged automatically. ## Install ```bash pip install claude-ctx ctx-init # terminal wizard: hooks, graph, model, harness goal ctx-init --graph --hooks --model-mode skip # fast runtime graph + Claude Code hooks ctx-init --graph --graph-install-mode full # expand the full markdown wiki locally ctx-init --wizard # force the same wizard from scripts/tests ctx-init --model-mode custom --model openai/gpt-5.5 --goal "build a CAD agent" ``` Optional extras: `pip install "claude-ctx[embeddings]"` for the semantic backend, `pip install "claude-ctx[harness]"` for local/API model harness runs, `pip install "claude-ctx[dev]"` for the test toolchain. ### Pre-built knowledge graph Graph-backed recommendations need the pre-built graph. By default, `ctx-init --graph` installs the fast runtime artifact: `graph/wiki-graph-runtime.tar.gz` in source checkouts, or the matching GitHub release asset from pip installs. It contains `graphify-out/*`, the shipped skill index needed for recommendations, and the 16 harness pages needed by `ctx-harness-install`: ```bash ctx-init --graph ``` The full LLM-wiki artifact remains available for local browsing, Obsidian, and expanded markdown pages: ```bash ctx-init --graph --graph-install-mode full ``` The full `wiki-graph.tar.gz` includes the shipped skill index, 91,450 skill entity pages under `entities/skills/`, 89,465 hydrated installable `SKILL.md` files under `converted/`, and 16 harness pages under `entities/harnesses/`. > **Windows:** PowerShell's built-in `tar.exe` does not support > `--force-local`; use `tar -xzf graph\wiki-graph.tar.gz -C "$env:USERPROFILE\.claude\skill-wiki"`. > In Git Bash or MSYS, use `--force-local` only when your `-C` target is a > drive-letter path such as `C:/Users/...`. ## Use After `ctx-init --hooks` or the wizard hook step, ctx observes Claude Code's `PostToolUse` and `Stop` events. Typical flow: ```bash ctx-scan-repo --repo . # scan current repo and stack signals ctx-scan-repo --repo . --recommend # include skill/agent/MCP recommendations ctx-agent-add --agent-path ./code-reviewer.md --name code-reviewer ctx-harness-add --repo https://github.com/earthtojake/text-to-cad --tag cad ctx-harness-install text-to-cad --dry-run # inspect before cloning/running anything ctx-harness-install text-to-cad # install after reviewing the plan ctx-harness-install text-to-cad --update --dry-run ctx-harness-install text-to-cad --uninstall --dry-run ctx-skill-quality list # four-signal quality score for every skill ctx-skill-quality explain python-patterns # drill into a single skill ctx-skill-health dashboard # structural health + drift detection ctx-toolbox run --event pre-commit # run a council on the current diff ctx-monitor serve # local dashboard: http://127.0.0.1:8765/ ``` Before pushing, run the local PR gate: ```bash python scripts/ci_preflight.py --profile pr ``` It uses the same changed-file classifier as GitHub Actions, then runs the matching local checks: stats, ruff, mypy, pip check, unit coverage, canaries, package build, twine, docs, graph validation, browser, and similarity gates as needed. Use `--profile full` before release work to force the source/package gates even for docs-only or graph-only changes. The **`ctx-monitor`** dashboard shows currently loaded skills, agents, MCP servers, installed harness records, and generic-harness validation/escalation state. It provides load/unload buttons where ctx owns the live action, a graph view (`/graph?slug=...`), the LLM-wiki entity browser (`/wiki/`), a filterable skills grid, a session timeline, audit/runtime log views, and a live SSE event stream. Installed harness records appear in `/loaded`; harness pages appear in `/wiki` and `/graph`. Harness install/update/uninstall actions stay in `ctx-harness-install`. When `ctx-skill-add`, `ctx-agent-add`, `ctx-mcp-add`, or `ctx-harness-add` finds an existing entity, ctx prints a benefits/risks update review and skips replacement by default. Re-run with `--update-existing` to apply the catalog or local asset update after review. Step-by-step entity onboarding: **** Full docs, architecture, and every module: **** ## License MIT — see [LICENSE](LICENSE).