scalpel

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

Use when working on scalpel-ipc, scalpel-alloc, shared memory ring buffer, Unix domain sockets, string interning protocol, custom GlobalAlloc, or any unsafe memory/IPC code

Use when working on scalpel-prune crate, Docker integration, SBOM generation, code removal logic, re-export chain resolution, or any code that modifies user source files

Use when working on scalpel-analyze crate, tree-sitter parsing, call graph construction, function extraction, import resolution, or debugging false positives in the genome

Use when working on scalpel-tracer crate, language probes in probes/ directory, coverage pipelines, event ingestion, resource attribution, or debugging missing trace events

Use after ANY change to analysis, merge, classification, or pruning logic. Also use before claiming accuracy improved or false positives fixed. Mandatory exit gate for all domain skills.

Run static analysis on a project directory and show results

Run CI pipeline checks (trace + score + optional diff)

Compare two genome exports to show what changed

Export the Code Genome in various formats

Query the Code Genome graph for analysis and debugging

Undo the last pruning operation

Compute and display the dependency health score

Start the interactive Code Genome visualization UI

Run scalpel trace against a test project and inspect the output

Run benchmarks and compare against performance budgets

Run pruning in audit mode against a test fixture and verify results

Run the full test suite with formatted output, or test a specific crate