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/aspenkit/aspens/doc-impactnpx skills add aspenkit/aspens --skill doc-impactgit clone --depth 1 https://github.com/aspenkit/aspensWhat 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 | $0.00032 | $0.01268 |
| Opus 5 | $0.00016 | $0.00634 |
| Sonnet 5 | $0.00006 | $0.00254 |
| Haiku 4.5 | $0.00003 | $0.00127 |
Grade A, and why
doc-impact 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 3d 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 — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are working on doc impact — the command that shows whether generated agent context is keeping up with the codebase, optionally interprets results via LLM, and can interactively apply recommended repairs.
Domain purpose
Audits the agent context generated by aspens against the live source tree, reports per-target health (Claude, Codex), and offers an interactive --apply flow that re-runs the right aspens doc init/sync variant to repair gaps. The LLM interpretation is a thin layer on top of deterministic metrics — the metrics are the contract.
Business rules / invariants
- Target inference: If
.aspens.jsonis absent, targets are inferred from scan results (.claude/→ claude,.agents/→ codex). Falls back to['claude']. - LLM is optional and tool-less. Runs only when a CLI backend is detected.
runLLMis invoked withdisableTools: true; prompt must return pure JSON (bottom_line,improves,risks,next_step). Failure is caught and reported as "Analysis unavailable" — never fatal. - Graph failure is non-fatal. If
buildRepoGraphthrows (or--no-graphis passed),graphisnulland hub coverage is skipped/n/a. - Hub coverage haystack is the code-map, not AGENTS.md. Post-Phase 1,
## Key Filesno longer lives in root instructions.computeHubCoveragereads.claude/code-map.md(claude) or.agents/skills/architecture/references/code-map.md(codex). If the code-map file is missing, it reportscodeMapMissing: trueinstead of spurious "missing hub" warnings. Older callers withoutrepoPathfall back to the legacycontextTexthaystack. - Health score deductions (start 100): missing instructions −35; no skills −25; domain gaps proportional up to −25; missed hubs −4 each; drift −3 per file (cap −20); unhealthy hooks −10 (hook-capable targets only); broken save-tokens −5 (claude only).
LOW_SIGNAL_DOMAIN_NAMES(config,test,tests,__tests__,spec,e2e) are excluded from coverage scoring but tracked inexcluded.SOURCE_EXTSextends the scanner set with.scala,.clj,.elm,.vue,.sveltefor drift detection. Adding a language for drift requires updating this set.- Walk depth capped at 5 — deep nested source files won't appear in drift analysis.
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.
- 3d ago First seen · 55 lines · 32 tokens per session scan A 26cff4bad863
doc-impact is a skill published in the GitHub repository aspenkit/aspens (96 stars, last pushed 18d ago), licensed MIT. It adds 32 tokens to every session and 1,268 once invoked, about $0.0002 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 2026-08-30.
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