Guidance
Steering
Use Kiro steering for project conventions, commands, architecture rules, and review expectations.
Kiro codebase context combines steering files, specifications, project files, and tools available to the agent. Graphify adds a persistent structural layer so Kiro can query dependencies, call paths, communities, and documentation instead of rebuilding its mental model from search. The Graphify Kiro installer writes a native skill and steering guidance, giving the agent a documented workflow for using graph artifacts.
Published Updated
Graphify stores inspectable artifacts so codebase knowledge can be reviewed by humans and reused by AI coding assistants.

Guidance
Use Kiro steering for project conventions, commands, architecture rules, and review expectations.
Workflow
The Graphify installer adds a Kiro skill that explains when and how to query project structure.
Structure
graph.json and GRAPH_REPORT.md carry relationships across Kiro sessions and specs.
Kiro codebase context is the project information Kiro can use while planning and implementing work. That includes steering guidance, specs, source files, tool results, and any graph or documentation artifacts exposed in the workspace. The context is strongest when intended behavior, working rules, and actual code relationships are all explicit rather than mixed into one long prompt. Better context selects fewer, more relevant files instead of asking the agent to remember everything.
Kiro steering carries durable project policy while a skill describes a reusable workflow. Neither is a substitute for a structural map: steering can say when to query the graph, and the graph can answer where a dependency or call path actually goes. This separation prevents a steering file from becoming a manually maintained architecture inventory that goes stale after every refactor.
Run graphify kiro install from the repository root after installing graphifyy. The installer creates the Graphify skill under .kiro/skills and adds Kiro steering guidance so the workflow is available in later sessions. Installation changes project guidance only; Kiro still needs a repository graph and a task that benefits from structural queries. Commit the generated project files when the team wants the same Graphify workflow on every machine.
Kiro should use graph.json for queryable structure and GRAPH_REPORT.md for a concise architecture briefing. graph.html is useful when a human wants to inspect relationships, while source files remain the authority for implementation details. The report is a context selector: it should tell Kiro which modules and source files deserve deeper reading.
Start from the symbols and modules named in the spec, then query reverse dependencies, call paths, and affected tests before writing a task list. This keeps the spec grounded in the repository's current structure instead of assuming a proposed design already exists. The resulting plan should distinguish existing relationships from relationships the implementation intends to create.
Refresh the graph after structural changes and after important specs or design documents change. Verify every graph-derived implementation claim in source and require Kiro to run the repository's type checks and tests before accepting a task. Store the graph revision or timestamp with the project guidance when several branches or long-running specs use the same repository.
graphify kiro install
graphify extract .
graphify path "ApiController" "BillingService"Yes. The current Graphify CLI includes graphify kiro install with a Kiro skill and steering integration.
No. Steering defines working policy; the graph stores project relationships and reusable structure.
Kiro supports MCP, but the documented Kiro installer is the stable file and steering integration. Add MCP only when the team operates a compatible graph server.
Refresh after file moves, interface changes, major refactors, dependency updates, and meaningful spec or design-document changes.
Continue through the Graphify topic cluster with pages that explain assistant context, architecture review, documentation, and graph-based codebase understanding.
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Give Codex persistent codebase context with graph artifacts, concise AGENTS.md rules, and MCP tools so repository questions use structure, not repeated scans.
AGENTS.md vs a codebase knowledge graph
Compare AGENTS.md instructions with a codebase knowledge graph, see what each layer stores, and learn how to combine them for persistent AI coding context.
Start from the use cases page or upload a project ZIP to build a graph that your team can inspect and reuse.