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- Node.js and npm installed
- Access to a project with `docs/specs/[ID]/` folder structure
- Developer Kit installed
How to use knowledge-graph
- 1.Install the skill via npx skills add
- 2.Call read-knowledge-graph with a spec folder path to load cached discoveries
- 3.Use query-knowledge-graph to search for specific components, patterns, or APIs
- 4.Call update-knowledge-graph after agent discoveries to persist new findings
- 5.Run validate-against-knowledge-graph before task implementation to check dependencies
- 6.Use validate-contract to verify provides/expects between tasks match actual implementations
Use cases
- 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
- 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
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.
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.
No. The skill only creates and updates knowledge-graph.json files in docs/specs/[ID]/ folders. It never modifies actual source code files.
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.
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:
- spec-to-tasks needs to cache/reuse codebase analysis - Store agent discoveries for future reuse
- task-implementation needs to validate task dependencies and contracts - Check if required components exist before implementing
- Any command needs to query existing patterns/components/APIs - Retrieve cached codebase context
- 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.jsonfiles. - 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
- schema.md - Complete JSON schema
- query-examples.md - Query patterns
- integration-patterns.md - Command integration
- error-handling.md - Error handling guide
- performance.md - Performance optimization
- security.md - Security considerations
- examples.md - Practical examples
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