checkup
Skill2 starsChanged 3 months agoMITView on GitHub
Run the canonical, already-optimal project checkup in one command — policy presence, directives health, per-component metrics, infra tips, duplication, and drift detection — so you never have to hand-write a good checkup prompt. Use when the user says "do a complete checkup", "botte doctor", after a component update, when onboarding to a project, or when multiple agents/devs may have caused drift.
7 other projects use a version of this, 1 of them edited.
Adopted by
Most recently taken up by
- BermanRoman/promt-seo-geotheir own version, first seen Nov 8, 2026
- zedarvates/frugal-skillsedited, first seen Nov 8, 2026
- egregore-labs/egregoretheir own version, first seen Nov 6, 2026
- johnviklund/agent-skillstheir own version, first seen Sep 12, 2026
- rainstorm0907/claude-checkuptheir own version, first seen Aug 12, 2026
- agentvitals/checkuptheir own version, first seen Jul 28, 2026
Other versions7 projects use a version of this.
Word for word · 0
None found.
Edited · 1
- zedarvates/frugal-skills★ 148% same
Wrote their own version · 6
- egregore-labs/egregore★ 293same name
- agentvitals/checkup★ 95same name
- johnviklund/agent-skills★ 2same name
- tokyubevoxelverse/checkup★ 1same name
- BermanRoman/promt-seo-geo★ 0same name
- rainstorm0907/claude-checkup★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository75 other files it gives its agents.
- AGENTS.mdAGENTS.md
- clean-cacheSkill
- agent-cacheSkill
- app_testSkill
- asset-qualitySkill
- auto_distillSkill
- auto-memorySkill
- auto_routerSkill
- benchSkill
- bootstrapSkill
- botte-proxySkill
- cacheSkill
- capabilitiesSkill
- cardinalSkill
- cavemanSkill
- clarificationSkill
- clusterSkill
- code_fingerprintSkill
- completion_proofSkill
- conductorSkill
- context_budgetSkill
- context_profilerSkill
- context_slicerSkill
- context_windowsSkill
- control_loopSkill
- cost_estimatorSkill
- cwe_kbSkill
- dag_optimizerSkill
- dashboardSkill
- decision-ladderSkill
- demoSkill
- diff_languageSkill
- directives_auditSkill
- docgenSkill
- docs_stewardSkill
- eventsSkill
- fallow_likeSkill
- fast_contextSkill
- fixSkill
- harness_deltaSkill
- hermes-bridgeSkill
- hf_provenanceSkill
- infra_advisorSkill
- ingestSkill
- llm_backendsSkill
- llm_mcpSkill
- loaderSkill
- mcp_gatewaySkill
- meta_harnessSkill
- metricsSkill
- migration_auditSkill
- monte_cristoSkill
- mousquetairesSkill
- nlp_deterministicSkill
- nn_auditSkill
- prefix-prunerSkill
- prefix_treeSkill
- preflightSkill
- prompt_improverSkill
- reportSkill
- The first 60 shown.
The file
Files
checkup — the canonical project checkup ("botte doctor")
So a "complete checkup" doesn't depend on you writing a good prompt: one command runs the standard sequence in the right order and prints a single verdict, all local / 0 cloud tokens.
python -m skills.checkup.cli # current dir
python -m skills.checkup.cli <project> --json
python -m skills.checkup.cli . --pr-comment # Markdown verdict for a PR comment
python -m skills.checkup.cli . --doctor # + machine scan + ranked top-3 opportunities
python -m skills.checkup.cli . --doctor --fresh # re-scan for local LLM backends (not cached)--doctor — the one-verb assembly
--doctor is checkup plus two things it doesn't otherwise do:
- machine scan — is a local LLM backend reachable (LM Studio/Ollama)? via
[[llm_backends]]
audit(); reads the cached registry unless--fresh. - ranked top-3 opportunities — fixes from [[fix]]
find_fixes(), ranked by estimated token cost (highest first), plus any remaining drift items, capped at 3.
Both feed a one-line verdict: ✅ sain when there's no drift and a local
backend is active, or ⚠️ N optimisation(s), ~X tokens d'opportunités
otherwise. Pure assembly of existing modules — no new skill, no new report format.
Sequence (cheap → deeper)
- policy — is
.botte/policy.mdcommitted? (shared rules for devs/agents) - directives — CLAUDE.md/AGENTS.md health + stale path refs
- metrics — LOC per component + always-on cost + savings framing
- infra — hardware/software/MCP cluster tips (+ ASCII diagram)
- duplication — stdlib AST duplicate-function scan
- security — taint / data-flow scan ([[fallow_like]]
TaintAnalyzer), CWE-tagged; high-severity findings become drift. 0 cloud tokens. - drift — MCP wired? directives stale/oversized? policy missing? security?
Then points at the deep code audit (secrets/dead-code) for when you want it.
Why
A component update or another dev/agent introduces drift — stale directives,
unwired MCP, an oversized CLAUDE.md, a missing policy. /checkup catches all of
it in one pass, with a fixed optimal procedure, instead of an ad-hoc prompt that
may be sub-optimal and may not prioritise local models.
On pull requests
--pr-comment prints a verdict-first Markdown comment (carrying a stable marker
so a bot can edit it in place), including the security section — so the
taint/data-flow scan rides into CI for free. The 🧦 Botte Checkup (PR) GitHub
Action (.github/workflows/botte-pr-checkup.yml) runs this on every PR and
posts/updates a single comment via gh — 0 cloud tokens, no extra dependencies.
The workflow sets BOTTE_CHECKUP_CONTEXT=github-pr, so machine-local MCP wiring
is reported as not applicable instead of impossible CI drift; local checkups
still flag missing wiring. Any project that deployed botte-secrète can reuse the
same workflow.
Related: [[preflight]] (enforces prefer-local every turn), [[infra_advisor]], [[metrics]], [[directives_audit]], [[bootstrap]].
Does it work?
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People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

