Borrowing it
Nothing to install: this file belongs to jeetkhinde/ai-stack. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/jeetkhinde/ai-stack/master/.gemini/skills/review-changes/SKILL.mdgit clone --depth 1 https://github.com/jeetkhinde/ai-stackWrote 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/jeetkhinde/ai-stack/review-changes)<a href="https://agentmods.dev/skills/jeetkhinde/ai-stack/review-changes"><img src="https://agentmods.dev/badge/skills/jeetkhinde/ai-stack/review-changes/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/jeetkhinde/ai-stack/review-changes"><img src="https://agentmods.dev/badge/skills/jeetkhinde/ai-stack/review-changes.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 | $0.00014 | $0.00237 |
| Opus 5.5 | $0.00006 | $0.00095 |
| Sonnet 5.5 | $0.00003 | $0.00047 |
| Haiku 4.5 | $0.00001 | $0.00024 |
Grade A, and why
review-changes 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 14d 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.
This is a copy
86% identical to review-changes — 26 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Review Changes
Perform a thorough, risk-aware code review using the knowledge graph.
Steps
- Run
detect_changesto get risk-scored change analysis. - Run
get_affected_flowsto find impacted execution paths. - For each high-risk function, run
query_graphwith pattern="tests_for" to check test coverage. - Run
get_impact_radiusto understand the blast radius. - For any untested changes, suggest specific test cases.
Output Format
Provide findings grouped by risk level (high/medium/low) with:
- What changed and why it matters
- Test coverage status
- Suggested improvements
- Overall merge recommendation
Token Efficiency Rules
- ALWAYS start with
get_minimal_context(task="<your task>")before any other graph tool. - Use
detail_level="minimal"on all calls. Only escalate to "standard" when minimal is insufficient. - Target: complete any review/debug/refactor task in ≤5 tool calls and ≤800 total output tokens.
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.
- 14d ago First seen · 30 lines · 14 tokens per session scan A 84372ff46190
review-changes is a skill published in the GitHub repository jeetkhinde/ai-stack (0 stars, last pushed 20d ago), licensed MIT. It adds 14 tokens to every session and 237 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 86% identical to review-changes, differing in 26 lines, and is treated as a copy.
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Guide the user through a quadrant walk that maps the unknowns of a task — open by listing the known knowns, then work through known unknowns, unknown knowns, and unknown unknowns one stage at a time, ending with a complete four-quadrant map in the user's hands. Use when a request is ambiguous or underspecified, the…
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