Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add JavanC/Homunculus --skill purpose-reviewgit clone --depth 1 https://github.com/JavanC/HomunculusWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/javanc/homunculus/purpose-review)<a href="https://agentmods.dev/skills/javanc/homunculus/purpose-review"><img src="https://agentmods.dev/badge/skills/javanc/homunculus/purpose-review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/javanc/homunculus/purpose-review"><img src="https://agentmods.dev/badge/skills/javanc/homunculus/purpose-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00071 | $0.02940 |
| Opus 5.5 | $0.00028 | $0.01176 |
| Sonnet 5.5 | $0.00014 | $0.00588 |
| Haiku 4.5 | $0.00007 | $0.00294 |
Grade A, and why
purpose-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Build or review a project's purpose tree. Uses the purpose-tree method; read it first. Runs only when the human asks — it may change purposes, so the human must be present.
Session-end checks belong to purpose-sync. This skill covers what a single session
cannot see.
Step 1 — Collect facts
node <this-skill>/scripts/review.cjs --run-checks
--run-checks runs each node's health_check command (30 s limit each). These are the
project's own commands; if any looks destructive, run without the flag and ask first.
The output's mode decides the next step.
Bootstrap (mode: bootstrap — no tree yet)
The AI may draft the root and first layer, labeled by source. The human confirms every line. Do not open with "Why does this project exist?" when the repo has material to draft from.
- Read first. Read every file in
intent_docs(README, CLAUDE.md/AGENTS.md, product brief, ADRs, docs/) and the fullinventory, including each entry'sareas(one level deeper, e.g.src/compliance/). Every area must end up under a purpose or a gap line. - Draft the root and first layer together. Root = one sentence of why. First layer =
3–6 purposes that serve the root, each with the inventory entries/areas that realize it.
Every line carries its source:
(from doc: README.md:3)or(inferred from code: src/sync/). - Self-check the draft before showing it. Fix, don't just note:
- Means as purposes. A proposed purpose that names a tool, product, platform, or
file ("iOS app + Supabase", "subscription", "the CLI") is a means: move it into the
realized_byof the purpose it serves. - Sibling overlap. Two siblings that would be satisfied by the same work are one purpose: merge them.
- Mixed root. If the root sentence also carries origin story, constraints, or
targets, split them out: constraints/targets →
metricsor children; background →status_note. The root keeps only the why. - Coverage. Inventory areas that fit no purpose go under a gap line, not into an invented purpose.
- Means as purposes. A proposed purpose that names a tool, product, platform, or
file ("iOS app + Supabase", "subscription", "the CLI") is a means: move it into the
- Ask what code cannot show. If any draft line is inferred from code, add direct questions for what code cannot reveal: profit or revenue goal, the owner's own use, community or audience, purposes not built yet.
- Show root + first layer + gaps + questions as one numbered list and ask once: "Accept all? (or e.g. 'reject 2', '3: reword to …')". Unanswered items count as rejected. A rejected or unanswered root means no tree yet: ask for the root in one sentence.
- Write
purpose-tree.yamlfrom the template with the accepted nodes, setlast_synced:to the currentHEAD, and validate. Do not draft deeper levels now; a later full review grows them (purpose-structure pass).purpose-syncnever adds purposes.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday Changed · +90 lines 6e42c3ad72d9
- 9d ago First seen · 98 lines · 71 tokens per session scan A d6b2ce976e2c
purpose-review is a skill published in the GitHub repository JavanC/Homunculus (15 stars, last pushed yesterday), licensed MIT. It adds 71 tokens to every session and 2,940 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-22.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…