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 mhashim6/kauri --skill reviewgit clone --depth 1 https://github.com/mhashim6/kauriWrote 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/mhashim6/kauri/review)<a href="https://agentmods.dev/skills/mhashim6/kauri/review"><img src="https://agentmods.dev/badge/skills/mhashim6/kauri/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/mhashim6/kauri/review"><img src="https://agentmods.dev/badge/skills/mhashim6/kauri/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 | $0.00039 | $0.00545 |
| Opus 5.5 | $0.00016 | $0.00218 |
| Sonnet 5.5 | $0.00008 | $0.00109 |
| Haiku 4.5 | $0.00004 | $0.00055 |
Grade A, and why
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 1mo 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.
What it actually says
Review Changes Against Decisions
After implementing changes, verify they are consistent with recorded project decisions. This catches violations before they're committed.
Steps
-
Identify what changed: If
$ARGUMENTSis a file path, read it. If it's a commit range, rungit diff $ARGUMENTS. If empty, rungit diffto see unstaged changes, orgit diff --cachedfor staged changes. -
Find related decisions: For each changed file, query Kauri:
kauri_querywith--file <path>for directly associated decisions.kauri_querywith--textusing keywords from the changed code (function names, module names, concepts).
-
Read the full decisions: Call
kauri_show <id>for every match. Don't skip any — a decision might look irrelevant from the title but contain a constraint in the body. -
Assess consistency: For each relevant decision, determine:
- Consistent: The changes respect the decision. Note this.
- Potential conflict: The changes might violate the decision. Explain specifically what conflicts and why.
- Decision should be updated: The changes are intentional improvements that make the old decision obsolete.
-
Report to the user:
- List each relevant decision and your assessment.
- For conflicts: recommend either adjusting the code or superseding the decision.
- For decisions that should be updated: offer to record a superseding
decision via
/kauri:propose. - For decisions now validated by the changes: offer to run
kauri_validate still_validto refresh their timestamp.
When to use this
- Before
git commiton significant changes - When reviewing a PR or diff
- When the user asks "does this look right?" or "anything I'm missing?"
- After refactoring that touches many files
- When the post-commit staleness hook reports stale decisions
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.
- 1mo ago First seen · 53 lines · 39 tokens per session scan A f99f7069fd9e
review is a skill published in the GitHub repository mhashim6/kauri (5 stars, last pushed 6mo ago), licensed MIT. It adds 39 tokens to every session and 545 once invoked, about $0.0002 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 2026-08-31.
Other skills, from other repositories
code-review
A code-review procedure for examining supplied code or a change diff for evidence-based bugs, compatibility problems, and data risks.
github-code-review
Review PRs: diffs, inline comments via gh or REST.
simplify-code
Sequential 3-lens cleanup of recent code changes.
requesting-code-review
Pre-commit review: security scan, quality gates, auto-fix.
ADR Decision Quality
Ensure ADRs capture context, decision, alternatives, tradeoffs, and follow-ups in a way that prevents future drift.
pragma-code-review
A code-review guide written in Chinese. It reviews code across correctness, architectural boundaries, risk, and verification.