mx-report
Skill2 starsChanged 4 months agoMITView on GitHub
MutantX Phase 4 — Calculate mutation score and generate a detailed report with test gap analysis.
In this repository12 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- mutateSkill
- mx-detectSkill
- mx-generateSkill
- mx-testSkill
- mx-validateSkill
- mutateSkill
- mx-detectSkill
- mx-generateSkill
- mx-reportSkill
- mx-testSkill
- mx-validateSkill
The file
We split this skill into the rules it gives an agent
5 rules. About 0 are common, 3 are distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 31
After the script runs, read .mutants/report.md.
- Distinctive: line 35
Read the patch diff shown in the report.
- Distinctive: line 36
Read the relevant source file to understand the surrounding code context.
- Distinctive: line 37
Add these two sections after the diff block:
- Very specific: line 45
Add a ## Recommendations section at the end of the report with 2-5 bullet points summarizing the most important test gaps found.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
MutantX — Phase 4: Reporting
This phase has two layers:
- Deterministic (Python script) — calculates scores, generates summary tables, includes patch diffs for survived mutants
- AI analysis (this skill) — reads the report and adds "why this matters" explanations, suggested tests, and prioritized recommendations
Step 1: Run the Deterministic Report Script
Locate and execute mx-report.py:
python3 <path-to-mx-report.py> --mutants-dir .mutantsFind mx-report.py by checking these locations in order:
./src/scripts/mx-report.py(if inside the MutantX repo)~/.claude/scripts/mx-report.py(global install)
This generates .mutants/report.md with summary statistics, survived mutant patches, killed mutant table, and updates the manifest summary. Display the script's output to the user.
Step 2: AI Analysis of Survived Mutants
After the script runs, read .mutants/report.md. For each survived mutant section (marked with <!-- AI analysis --> comments), replace the comment with:
For each survived mutant:
- Read the patch diff shown in the report.
- Read the relevant source file to understand the surrounding code context.
- Add these two sections after the diff block:
Why this matters: A brief explanation of what kind of bug this mutation represents and what could go wrong in production if this bug existed. Be specific to the actual code, not generic.
Suggested test: A concrete, copy-pasteable test case (in the project's language and test framework) that would catch this mutant. Use realistic test names and assertions.
After all survived mutants:
Add a ## Recommendations section at the end of the report with 2-5 bullet points summarizing the most important test gaps found. Be specific — reference file names and functionality, not generic advice.
Step 3: Present Results
Display a concise summary to the user:
Mutation Testing Complete!
Score: 84% (16 killed / 19 testable)
Survived: 3 mutants — see .mutants/report.md for details
Top gaps:
- src/billing.ts: price rounding logic has no edge case tests
- src/auth.ts: token expiry check can be bypassedDoes it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

