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/a7um/zero-review/auto-reqnpx skills add A7um/zero-review --skill auto-reqgit clone --depth 1 https://github.com/A7um/zero-reviewWhat 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 | $0.00024 | $0.01514 |
| Opus 5 | $0.00012 | $0.00757 |
| Sonnet 5 | $0.00005 | $0.00303 |
| Haiku 4.5 | $0.00002 | $0.00151 |
Grade A, and why
auto-req 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Auto-Req Skill
WHEN TO USE: You have raw human input (conversation, issue, brief, vague request) and need to produce a structured requirements document before development or testing can begin.
Elicitation Philosophy
Understand what people mean, not just what they say. Clarity comes from asking, not assuming.
① Capture intent, not words — The sponsor's phrasing is a starting point, not a spec. Your job is to extract the underlying goal. "Make the dashboard faster" might mean "reduce load time," "simplify the layout," or "remove features I don't use." Ask which.
② Separate problem from solution — Requirements describe what and why, never how. If the sponsor says "add a Redis cache," the requirement is "reduce API response time below 200ms." The implementation choice belongs to the dev agent.
③ Every requirement must be verifiable — If you can't describe how to check whether a requirement is met, it isn't a requirement yet. "Improve UX" fails. "User can complete checkout in under 3 clicks" passes.
④ Silence is ambiguity — What the sponsor didn't say matters as much as what they did. Missing constraints, unmentioned users, omitted error cases — these are gaps, not implicit "don't cares." Surface them.
⑤ Done means actionable — A requirements doc is complete when a dev agent can read it and begin work without asking for clarification. Not when every conceivable detail is specified — when every necessary detail is.
Strategy Selection
| Starting material | Strategy |
|---|---|
| Vague or conversational request, sponsor available for back-and-forth | strategies/elicit-from-vague.md |
| Vague or conversational request, prefer minimal interaction | strategies/propose-from-assumptions.md |
| Existing written spec, PRD, or detailed description that needs sharpening | strategies/refine-existing.md |
| GitHub issue, bug report, or user feedback that needs requirements extraction | strategies/extract-from-issue.md |
What ships with it
7 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.
- 2d ago First seen · 106 lines · 24 tokens per session scan A db7b253efdde
auto-req is a skill published in the GitHub repository A7um/zero-review (45 stars, last pushed 2mo ago), licensed MIT. It adds 24 tokens to every session and 1,514 once invoked, about $0.0001 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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