Augment
Self-healing, self-learning Claude Code setup — finds, installs, or forges the skills, hooks & MCP your project needs, in real time. Pairs with nodo.
npx -y skills add shivae372/claude-bootstrap --skill augmentAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
What its author says it does
Copied from the file, not written here
Gives this project a NEW capability on demand. Use the moment the user needs something the current setup can't do well — a new framework, a service integration (Stripe, Postgres, Twilio…), a deploy target, a niche workflow. Searches the open ecosystem for a fitting skill/MCP across platforms, installs the best vetted one, and if nothing fits, forges a bespoke skill. Triggers: 'can you also…', 'I need to…', 'set up…', 'integrate…', 'how do I … here', or any task with no matching installed skill.
SKILL.md
5.1 KB, as published. Nobody here has run it
Purpose
Close the gap between what the user wants and what this setup can do — in the moment, without them leaving the conversation. This is the engine that makes a fresh Claude Code project grow into exactly the toolkit THIS user needs.
When to use this
- The user asks for a capability with no matching skill/command/agent (check the
capability manifest:
python3 .claude/engine/doctor.py --manifest). - A
[gap]nudge was injected by the real-time hook (.claude/state/needs.jsonl). - The user explicitly says "augment", "find a skill for…", "add support for…".
Steps
1. Name the capability precisely
Restate what's missing as a short search phrase (e.g. "stripe payments", "deploy to fly.io", "supabase row level security"). Confirm with the user in one line.
2. Search the open ecosystem (across platforms)
python3 .claude/engine/skill_finder.py "<capability>" --json
This queries, in parallel and offline-tolerant: Anthropic's official skills,
GitHub (topic + repo search), the MCP Registry, and Smithery (if SMITHERY_API_KEY
is set). Results come back ranked by relevance with a trust score and flags.
Set GITHUB_TOKEN first if available — it lifts GitHub's rate limit.
3. Vet before you trust (never auto-install blindly)
Reject or down-rank a candidate that is: brand-new (<30d) with no stars, has a vague
or missing description, grants Bash with no constraint, or fetches remote code at
runtime. Prefer: official (anthropic/skills), verified (Smithery), pinned commit
SHAs, and repos with real usage. Show the user the top 1–3 with their trust/flags and
let them pick when it's a close call.
4a. Install a good match
- Official skill / plugin: add it with
/marketplace(enter<owner/repo>when prompted), then/plugin install <name>@<marketplace>. - MCP server:
claude mcp add <name> ...(it activates next session — tell the user). Record it in.mcp.jsonso the team gets it too. - A SKILL.md in a repo: fetch it, read it end-to-end, then write it into
.claude/skills/<name>/SKILL.md. Validate:python3 .claude/engine/skill_forge.py validate <path>.
4b. Nothing fits → forge it
Invoke the forge skill to author a detailed, project-specific skill. Do NOT settle for a generic one — a vague skill is worse than none.
4c. Found it another way? Teach the finder (self-extending discovery)
If the web search missed it but you located the capability another way — a specific GitHub org, a vendor's own JSON search endpoint, or simply "X lives at Y" — record that source so the engine searches it next time TOO, alongside the web. Discovery then heals and compounds:
# a whole org that publishes the skills you needed:
echo '{"kind":"github_org","org":"<org>","note":"has <capability> skills/servers"}' \
| python3 .claude/engine/learn.py source-add
# or a queryable JSON endpoint, or a durable hint:
# {"kind":"http_json","name":"acme","url":"https://api.acme/s?q={query}","name_field":"slug","url_field":"link"}
# {"kind":"hint","name":"...","text":"For <X>, check <Y>"}
The next discovery run includes it automatically.
5. Make it real now, then learn
- Verify the new capability works (run it once if safe).
- Record what you added so the setup remembers:
echo '{"category":"stack","text":"Added <capability> via <skill/mcp>","tags":["augment"]}' \
| python3 .claude/engine/learn.py add
- Tell the user the new command/skill is live and how to use it.
Output
A new, working capability in .claude/ (skill, command, or MCP server), vetted and
validated, plus a one-line summary of what was added and how to invoke it.
Guardrails
- Never install a skill you haven't read. Never run a skill's setup script without inspecting it. Surface trust flags honestly.
- If discovery returns nothing and the domain is unfamiliar, ask the user one clarifying question rather than forging something generic.
Ecosystem note — codebase understanding → nodo
If the capability the user needs is understanding the codebase itself — architecture,
blast radius, "what calls X", dependency/call graph, where a concept lives — that's the
nodo sibling, not a web skill. If nodo is installed (.nodo/ or the /nodo skill exists),
use /nodo and read .nodo/nodo-context.json. If not, offer to install it from the same
marketplace: run /marketplace and enter shivae372/claude-bootstrap, then /plugin install nodo@claude-bootstrap
(or clone shivae372/nodo). claude-bootstrap reads nodo's map automatically at session start.