# Review Changes

> Perform a structured code review using change detection and impact

- Skill: `tirth8205/review-changes` (Agent Skill)
- Install (CLI): `npx skillmds@latest add tirth8205/review-changes`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tirth8205/review-changes/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: tirth8205 (https://skillmd.com/u/tirth8205)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/tirth8205/review-changes

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## Review Changes

Perform a thorough, risk-aware code review using the knowledge graph.

### Steps

1. Run `detect_changes_tool` to get risk-scored change analysis.
2. Run `get_affected_flows_tool` to find impacted execution paths.
3. For each high-risk function, run `query_graph_tool` with pattern="tests_for" to check test coverage.
4. Run `get_impact_radius_tool` to understand the blast radius.
5. 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
- Start with `get_minimal_context_tool(task="<your task>")` before other graph tools.
- 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.
- Read the implementation and its tests before changing code. The graph narrows scope; it does not replace the source.