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 agentmods add skills/duthaho/skillhub/mapnpx skills add duthaho/skillhub --skill mapgit clone --depth 1 https://github.com/duthaho/skillhubWhat 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 | $0.00217 | $0.01974 |
| Opus 5 | $0.00109 | $0.00987 |
| Sonnet 5 | $0.00043 | $0.00395 |
| Haiku 4.5 | $0.00022 | $0.00197 |
Grade A, and why
map 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 2d ago.
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 — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
map — orient the agent to an unfamiliar codebase
/map — map the whole repo into a lean AGENTS.md at its root
/map <subsystem> — deep-map one area, into a scoped section
/map refresh — re-check an existing map and update only what went stale
Answer one question: what would a competent engineer need to know before touching this repo — and nothing more? The strongest lever in agentic coding isn't a smarter model, it's better orientation: an agent that knows the entry points, the build commands, and the load-bearing conventions makes the right change; one that guesses edits the wrong layer.
Step 0 — Scope, and respect what exists
First, look before generating:
- Existing agent files? Check for
AGENTS.md,CLAUDE.md,.cursor/rules,.github/copilot-instructions.md. If one exists, this is a REFRESH, not a fresh write — read it, and update in place rather than duplicating. If aCLAUDE.mdalready carries the knowledge, offer to haveAGENTS.md@importit instead of restating it. If the existing map carries a stamp and HEAD has moved past it, state the drift in one line when naming the mode — "map is N commits behind (touched: X, Y)" viagit rev-list --count+git diff --statover<stamped-commit>..HEAD— and offer the refresh unless this run already is one. A stamp that no longer resolves (rebase, shallow clone) is itself the staleness signal: report it and offer a fresh map. Staleness surfaces at every touch, never only when someone remembers/map refresh. - Size the repo (
git ls-files | wc -l, top-level layout) to scale the fan-out: a small repo maps in one pass inline; a large or polyglot one gets the full parallel sweep below. - A subsystem argument (
/map the payment flow) narrows every step to that area and produces a scoped section, not a whole-repo rewrite.
State which mode you picked (NEW / REFRESH / FOCUS) and why.
Step 1 — Fan out along the read-first order
Dispatch read-only Explore sub-agents — one per lens — navigating by
grep/glob/read and following imports (no embeddings, no pre-index; always
fresh). This is the order practitioners converge on; run the lenses concurrently:
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.
- 2d ago First seen · 160 lines · 217 tokens per session scan A f86ccb26a22a
map is a skill published in the GitHub repository duthaho/skillhub (9 stars, last pushed 9d ago), licensed MIT. It adds 217 tokens to every session and 1,974 once invoked, about $0.0011 per session on Opus 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 2026-08-31.
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