What problem does it solve?
AI coding agents often make blind edits because they lack architectural context about a codebase. This Skill produces deep, implementation-ready engineering plans by combining GitNexus repository graph intelligence, statement-level Program Dependence Graph analysis, and targeted source verification, so a follow-up implementation agent can start work without re-investigating the repository.
Core Features & Use Cases
- Graph-guided planning: Uses GitNexus query, context, impact, and trace tools to map callers, callees, blast radius, and execution flows before proposing changes.
- Statement-level PDG slices: Builds bounded control- and data-dependence slices for the functions central to a change, with dedicated security and performance analysis modes.
- Machine-readable context pack: Emits a 13-section plan with a versioned evidence-provenance snapshot (dirty-tree digest and cited-path manifest) that an executor agent consumes directly.
- Deepen mode: Strengthens an existing plan in place, re-verifying claims against a refreshed index and reconciling already-landed execution steps.
- Use Case: Run "/gitnexus-plan Add retry support to the ingestion pipeline" to receive a verified plan document at docs/plans/ with direct dependents, test scenarios, risks, and verification commands.
Quick Start
Ask your agent to run /gitnexus-plan followed by a task description, such as planning a bug fix or feature, after indexing the repository with npx gitnexus analyze.