Review ChangesSAFE
Local-first code intelligence graph for MCP and CLI. Builds a persistent map of your codebase so AI coding tools read only what matters, with benchmarked context reductions on reviews and large-repo workflows.
Overview
Local-first code intelligence graph for MCP and CLI. Builds a persistent map of your codebase so AI coding tools read only what matters, with benchmarked context reductions on reviews and large-repo workflows.
a9c894db76a7OBSERVED · 2026-10-06What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
--- name: review-changes description: Perform a structured code review using change detection and impact --- ## Review Changes Review a change set with risk scores and blast radius from the knowledge graph. ### Steps 1. Call `detect_changes_tool` for risk-scored changed functions, test gaps and affected flows. 2. Call `get_affected_flows_tool` only when you need the steps of an affected flow. 3. For each high-risk function, call `query_graph_tool` with `pattern="tests_for"` to check test coverage. 4. Call `get_impact_radius_tool` when the blast radius is not clear from step 1. 5. Suggest specific test cases for untested changes. ### Output Format Group findings by risk level (high, medium, low). For each finding give what changed and why it matters, its test coverage, and the suggested fix. End with a merge recommendation. ## Token Efficiency Rules - Call `get_minimal_context_tool(task="<your task>")` before any other graph tool. - Pass `detail_level="minimal"` wherever a tool accepts it. Use "standard" only when minimal is not enough. - Prefer a targeted `query_graph_tool` call over a broad listing call. - Budget: about five tool calls and 800 tokens of graph output per task. - Read the implementation and its tests before changing code. The graph narrows scope; it does not replace the source.
Trust audit
SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | NA |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (0)
No findings outside the package's declared scope.
Gates applied: no_behavioural_pass.
a9c894db76a7full audit observations/trust-audit/skill/tirth8205__review-changes.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-06 | a9c894db76a7 | SAFE | B | 89 | first audit |
Questions
What does the Review Changes skill do?
Local-first code intelligence graph for MCP and CLI. Builds a persistent map of your codebase so AI coding tools read only what matters, with benchmarked context reductions on reviews and large-repo workflows.
Is Review Changes safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can Review Changes access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (a9c894db76a7), read on 2026-10-06. The repository is watched, and a new audit runs when it changes — this is the first audit.