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 Codagent-AI/agent-skills --skill review-assumptionsgit clone --depth 1 https://github.com/Codagent-AI/agent-skillsWrote 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/codagent-ai/agent-skills/review-assumptions)<a href="https://agentmods.dev/skills/codagent-ai/agent-skills/review-assumptions"><img src="https://agentmods.dev/badge/skills/codagent-ai/agent-skills/review-assumptions/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/codagent-ai/agent-skills/review-assumptions"><img src="https://agentmods.dev/badge/skills/codagent-ai/agent-skills/review-assumptions.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 | $0.00065 | $0.00602 |
| Opus 5 | $0.00032 | $0.00301 |
| Sonnet 5 | $0.00013 | $0.00120 |
| Haiku 4.5 | $0.00006 | $0.00060 |
Grade A, and why
review-assumptions 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 9d 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 — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review Assumptions
Audit assumptions and context gaps from implementor session reports against the approved plan. Fix clear deviations, ask the user about product ambiguity, and preserve plan-quality gaps for the final summary.
Process
- Find the session reports and map each to its workflow iteration and exact task file using available
run metadata. Do not infer task identity from report order; label an unmappable report
task unknown. - Extract each risky or notable assumption and each context gap. Give every finding a stable identity and ensure none is silently dropped.
- Verify claims against the controlling artifacts and relevant source before choosing a disposition:
- Fix: a clear defect, omission, or deviation from the approved plan. Make the focused change directly, or delegate nontrivial implementation when the caller permits it.
- Ask: a product, scope, or UX decision that evidence cannot resolve. Use
codagent:ask-questions, one finding at a time, with context, practical options, impact, and a recommendation. Apply the user's answer before moving on. - Accept: the implementation matches the plan or the stated risk is intentionally acceptable.
- Defer: the issue is real but outside this review's authority; identify the owner or later decision needed.
- Context gap: the report explicitly says the plan lacked information. Do not invent a resolution; surface what future planning needed to provide.
- Before reporting, reconcile the dispositions with the extracted findings.
Treat implementor statements as claims, not evidence. Inspect the cited code or artifacts before asserting that something is fixed or already handled. Do not turn an ordinary assumption into a context gap merely to avoid resolving it.
Run relevant validation and commit applied changes using the project's conventions unless the caller explicitly owns validation or commits. Do not create an empty commit.
Report
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.
- 9d ago First seen · 66 lines · 65 tokens per session scan A 002d37f1bb1e
review-assumptions is a skill published in the GitHub repository Codagent-AI/agent-skills (30 stars, last pushed 1mo ago), licensed MIT. It adds 65 tokens to every session and 602 once invoked, about $0.0003 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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