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knowledge-graph

giuseppe-trisciuoglio/developer-kit

Persistent JSON knowledge graph for caching codebase analysis and validating task dependencies.

What is knowledge-graph?

Manages a persistent Knowledge Graph stored as JSON that caches codebase discoveries, patterns, components, and APIs to avoid redundant exploration. Use it when spec-to-tasks needs to reuse analysis, task-implementation must validate dependencies, or any command needs to query cached patterns and components.

  • Read and parse knowledge graphs from specification folders
  • Query specific sections (components, patterns, APIs) with filtering
  • Update knowledge graphs with new discoveries and merge findings
  • Validate task dependencies and contracts against cached codebase state
  • Extract symbols and provides from implemented files
  • Aggregate knowledge graphs across multiple specifications

How to install knowledge-graph

npx skills add https://github.com/giuseppe-trisciuoglio/developer-kit --skill knowledge-graph
Prerequisites
  • Node.js and npm installed
  • Access to a project with `docs/specs/[ID]/` folder structure
  • Developer Kit installed
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How to use knowledge-graph

  1. 1.Install the skill via npx skills add
  2. 2.Call read-knowledge-graph with a spec folder path to load cached discoveries
  3. 3.Use query-knowledge-graph to search for specific components, patterns, or APIs
  4. 4.Call update-knowledge-graph after agent discoveries to persist new findings
  5. 5.Run validate-against-knowledge-graph before task implementation to check dependencies
  6. 6.Use validate-contract to verify provides/expects between tasks match actual implementations

Use cases

Good for
  • Cache codebase analysis results to avoid re-exploring the same code across multiple agent runs
  • Validate that required components and APIs exist before implementing tasks
  • Share discovered patterns and architectural conventions across team members
  • Check component dependencies before task generation to catch missing contracts early
  • Merge insights from multiple specification analyses into a global knowledge base
Who it's for
  • Development teams using agent-driven spec-to-code workflows
  • Architects designing multi-task specifications with interdependencies
  • Teams needing to validate task contracts and component availability
  • Projects with large codebases where redundant analysis is costly

knowledge-graph FAQ

What happens if the knowledge graph doesn't exist yet?

The skill will create a new knowledge-graph.json file in the spec folder when you first call update-knowledge-graph. You can also initialize it manually with the schema from references/schema.md.

How do I know if my knowledge graph is stale?

The skill tracks freshness: < 7 days is fresh, 7-30 days is stale (warning), > 30 days is very stale (offer regeneration). Check the metadata.updated_at timestamp in the KG file.

Can this skill modify my source code?

No. The skill only creates and updates knowledge-graph.json files in docs/specs/[ID]/ folders. It never modifies actual source code files.

What if the knowledge graph says a component exists but it doesn't in the actual codebase?

This indicates the KG is outdated. Regenerate it by re-running codebase analysis and calling update-knowledge-graph with fresh discoveries. The skill warns when KG is stale.

Can I use one knowledge graph for multiple specifications?

Each spec has its own primary KG in docs/specs/[ID]/knowledge-graph.json. Use aggregate-knowledge-graphs to merge patterns across specs into a global view.

Full instructions (SKILL.md)

Source of truth, from giuseppe-trisciuoglio/developer-kit.


name: knowledge-graph description: "Manage persistent Knowledge Graph for specifications. Provides read, query, update, and validation capabilities for codebase analysis caching. Use when: spec-to-tasks needs to cache/reuse codebase analysis, task-implementation needs to validate task dependencies or contracts, spec-quality needs to synchronize provides, or any command needs to query existing patterns/components/APIs. Reduces redundant codebase exploration by caching agent discoveries." allowed-tools: Read, Write, Edit, Grep, Glob, Bash

Knowledge Graph Skill

Overview

The Knowledge Graph (KG) is a persistent JSON file that stores discoveries from codebase analysis, eliminating redundant exploration and enabling task validation.

Location: docs/specs/[ID-feature]/knowledge-graph.json

Key Benefits:

  • ✅ Avoid re-exploring already-analyzed codebases
  • ✅ Validate task dependencies against actual codebase state
  • ✅ Share discoveries across team members
  • ✅ Accelerate task generation with cached context

When to Use

Use this skill when:

  1. spec-to-tasks needs to cache/reuse codebase analysis - Store agent discoveries for future reuse
  2. task-implementation needs to validate task dependencies and contracts - Check if required components exist before implementing
  3. Any command needs to query existing patterns/components/APIs - Retrieve cached codebase context
  4. Reducing redundant codebase exploration - Avoid re-analyzing already-explored code

Trigger phrases:

  • "Load knowledge graph"
  • "Query knowledge graph"
  • "Update knowledge graph"
  • "Validate against knowledge graph"
  • "Check if component exists"
  • "Find existing patterns"

Instructions

Available Operations

1. read-knowledge-graph - Load and parse KG for a specification

  • Input: Path to spec folder (e.g., docs/specs/001-feature/)
  • Output: KG object with metadata, patterns, components, APIs

2. query-knowledge-graph - Query specific sections (components, patterns, APIs)

  • Input: Spec folder, query type, optional filters
  • Output: Filtered results matching criteria

3. update-knowledge-graph - Update KG with new discoveries

  • Input: Spec folder, updates (partial KG), source description
  • Output: Merged KG with new findings

4. validate-against-knowledge-graph - Validate task dependencies against KG

  • Input: Spec folder, requirements (components, APIs, patterns)
  • Output: Validation report with errors/warnings

5. validate-contract - Validate provides/expects between tasks

  • Input: Spec folder, expects (files + symbols), completed dependencies
  • Output: Satisfied/unsatisfied expectations report

6. extract-provides - Extract symbols from implemented files

  • Input: Array of file paths
  • Output: Array of provides with file, symbols, type

7. aggregate-knowledge-graphs - Merge patterns from all specs

  • Input: Project root path
  • Output: Global KG with deduplicated patterns

See references/query-examples.md for detailed usage examples.

Examples

Input/Output Examples

Read Knowledge Graph:

Input: /knowledge-graph read docs/specs/001-hotel-search/
Output: {
  metadata: { spec_id: "001-hotel-search", version: "1.0" },
  patterns: { architectural: [...], conventions: [...] },
  components: { controllers: [...], services: [...]}
}

Query Components:

Input: /knowledge-graph query docs/specs/001-hotel-search/ components {"category": "services"}
Output: [{ id: "comp-svc-001", name: "HotelSearchService", type: "service"}]

Update Knowledge Graph:

Input: /knowledge-graph update docs/specs/001-hotel-search/ {
  patterns: { architectural: [{ name: "Repository Pattern"}] }
}
Output: "Added 1 pattern to knowledge graph"

Validate Dependencies:

Input: /knowledge-graph validate docs/specs/001-hotel-search/ {
  components: ["comp-repo-001"]
}
Output: { valid: true, errors: [], warnings: [] }

See references/examples.md for comprehensive workflow examples.

KG Schema Reference

See references/schema.md for complete JSON schema with examples.

Integration Patterns

See references/integration-patterns.md for detailed integration with Developer Kit commands.

Error Handling

See references/error-handling.md for comprehensive error handling strategies and recovery procedures.

Performance Considerations

See references/performance.md for optimization strategies and performance characteristics.

Security

See references/security.md for security considerations, threat mitigation, and best practices.

Best Practices

When to Query KG: Before codebase analysis, task generation, dependency validation

When to Update KG: After agent discoveries, component implementation, pattern discovery

KG Freshness:

  • < 7 days: Fresh
  • 7-30 days: Stale, warn user
  • 30 days: Very stale, offer regeneration

See references/performance.md and references/security.md for detailed best practices.

Constraints and Warnings

Critical Constraints

  • Source-Code Safe Operations: Does NOT modify source code files. Only creates/updates knowledge-graph.json files.
  • Path Validation: Only reads/writes KG files from docs/specs/[ID]/ paths.
  • No Automatic Code Generation: Caches analysis results, does NOT generate implementation code.

Limitations

  • Validation Scope: Checks components exist in KG, but cannot verify if they exist in actual codebase if KG is outdated
  • Freshness Dependency: KG accuracy depends on how recently it was updated
  • Single-Spec First: Each KG is primarily specific to a single specification
  • File Size: KG files can grow large (>1MB) for complex specifications

See references/error-handling.md and references/security.md for complete constraints and warnings.

Reference Files