بنقرة واحدة
graph-query
Query the Code Genome graph for analysis and debugging
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
القائمة
Query the Code Genome graph for analysis and debugging
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
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
| name | graph-query |
| description | Query the Code Genome graph for analysis and debugging |
| argument-hint | <natural-language-query> |
| allowed-tools | Bash, Read |
Query the Code Genome graph. Translate the natural language query into a scalpel CLI command.
Available query patterns:
cargo run -p scalpel-cli -- export .scalpel/coverage | jq '.edges[] | select(.target_name | contains("X"))'cargo run -p scalpel-cli -- export .scalpel/coverage | jq '.edges[] | select(.source_name | contains("X"))'cargo run -p scalpel-cli -- prune-report .scalpel/coveragecargo run -p scalpel-cli -- score --coverage-dir .scalpel/coveragecargo run -p scalpel-cli -- score --coverage-dir .scalpel/coveragecargo run -p scalpel-cli -- export .scalpel/coverage | jq '.nodes | sort_by(-.call_count) | .[0:10]'If the query doesn't match a pattern, export the genome as JSON and use jq to answer it. Present results in a readable format with context about what was found.