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Run pruning in audit mode against a test fixture and verify results
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| name | prune |
| description | Run pruning in audit mode against a test fixture and verify results |
| argument-hint | ["test-fixture-name"] |
| allowed-tools | Bash, Read |
Run Scalpel's prune command in audit mode against a test fixture.
tests/fixtures/$ARGUMENTS/.scalpel/genome.bincargo run -p scalpel-cli -- prune --mode audit --genome tests/fixtures/$ARGUMENTS/.scalpel/genome.bin
cd tests/fixtures/$ARGUMENTS && npm test
Call graph soundness framework: 9 pattern families, 10 safety vetoes, soundness-vs-precision tradeoffs. Use before changing merge.rs, analyzer, or prune pipeline.
Assess if a CVE in a dep is reachable from project code using 15-signal union (runtime/static/external). Outputs audit trail. Security-grade, conservative.
Runtime+static consensus: 15-signal weights, modes, saturation curve. Scalpel's novel moat. Use before changing tracer merge, prune decision, or adding signal sources.
Use to validate Scalpel's pruning safety on any Python project. Analyzes a real-world Python project with test suite, identifies dead code, stubs it, then runs the full test suite to prove nothing broke. Invoke with: /prune-safety-test <project-url-or-path>
Use to validate ALL Scalpel capabilities on a real-world Python project — static analysis accuracy, genome building, reachability classification, pruning safety, and context generation. Invoke with: /validate-on-project <project-url-or-path>
Use when working on scalpel-core, scalpel-proto, Code Genome graph structure, hybrid merge logic, reachability algorithms, confidence classification, or edge resolution