graph-mutation-plan

To create a graph mutation plan, you compose a structured document with fields for summary, episodes, entity upserts, edge upserts, and invalidations. This ensures consistency and accuracy when indexing and updating project context in AI agents.

Stable entity keys are consistent patterns used to identify nodes like repositories, pull requests, and modules. They ensure graph mutations remain accurate and traceable across software development lifecycle indexing updates.

You need canonical vocabulary when applying graph mutations to ensure standard labels and edge types are used for entities and relationships. This maintains data integrity when indexing complex software project context.

Yes, graph mutation planning enforces evidence and confidence discipline alongside entity upserts and edge upserts. This allows you to track the reliability and source of software development context updates.

The best way to handle graph updates for merged pull requests is to compose a mutation plan using canonical labels and stable entity keys. The skill provides a worked example demonstrating how to index bug fixes and code changes accurately.

Yes, mutation plans include an invalidations field specifically to remove stale edges and entities. This ensures your software development ontology remains accurate and free of obsolete project context after updates.