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2677 Task 35 Project Memory 5d815826
ASecurity**Status**: ๐ฌ Research & Planning **Created**: 2025-01-23 **Version**: v6.0.0 **Priority**: High
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- Added October 11, 2026
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[](https://www.skillsdirectory.com/skills/tools-only-2677-task-35-project-memory-5d815826)# TASK-35: Project Knowledge Graph
**Status**: ๐ฌ Research & Planning
**Created**: 2025-01-23
**Version**: v6.0.0
**Priority**: High
## Summary
Unified Knowledge Graph that connects all project knowledge (tasks, SOPs, system docs) with an experiential memory layer (patterns, pitfalls, decisions, learnings). Single query surface: "What do we know about X?"
## Evolution from Original Concept
**Original**: Project Memory (another storage silo)
**Evolved**: Knowledge Graph (unified layer over ALL knowledge)
The insight: Navigator docs ARE project memory. The gap isn't storageโit's **discovery and relationships**.
## Vision
```
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ PROJECT KNOWLEDGE GRAPH โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค
โ โโโโโโโโโโโ โโโโโโโโโโโ โโโโโโโโโโโ โโโโโโโโโโโ โ
โ โ TASKS โโโโโถโ SOPs โโโโโโ SYSTEM โ โ MARKERS โ โ
โ โโโโโโฌโโโโโ โโโโโโฌโโโโโ โโโโโโฌโโโโโ โโโโโโฌโโโโโ โ
โ โโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโ โ
โ โผ โผ โ
โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโ โ
โ โ CONCEPTS โ โ
โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโ โ
โ โฒ โฒ โ
โ โโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโ โ
โ โโโโโโดโโโโโ โโโโโโดโโโโโ โโโโโโดโโโโโ โโโโโโดโโโโโ โ
โ โPATTERNS โ โPITFALLS โ โDECISIONSโ โLEARNINGSโ โ
โ โโโโโโโโโโโ โโโโโโโโโโโ โโโโโโโโโโโ โโโโโโโโโโโ โ
โ MEMORIES (experiential) โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
```
## Requirements
### R1: Graph Storage
- `.agent/knowledge/graph.json` - index (~1k tokens)
- `.agent/knowledge/memories/` - experiential learnings
- Hybrid: JSON for queries, Markdown for details
- Git-tracked (team can share)
### R2: Node Types
- **TASK** - implementation plans
- **SYSTEM** - architecture docs
- **SOP** - procedures
- **MARKER** - session snapshots
- **CONCEPT** - extracted topics (auth, testing, api)
- **MEMORY** - patterns, pitfalls, decisions, learnings
- **FILE** - codebase files
### R3: Edge Types (Relationships)
- `created-from` - SOP created from TASK
- `references` - doc A links to doc B
- `relates-to` - shared concepts (weighted)
- `implements` - TASK implements CONCEPT
- `learned-from` - MEMORY discovered in TASK
- `contradicts` - conflicting memories
- `validated-by` - MEMORY confirmed in TASK
- `supersedes` - new replaces old
### R4: Query Interface
```
"What do we know about auth?"
โ Returns: Tasks, SOPs, Memories, Files related to auth
"Any pitfalls for testing?"
โ Returns: Pitfall memories + related SOPs
"What decisions about architecture?"
โ Returns: Decision memories with rationale
```
### R5: Memory Capture
- Auto from corrections (nav-profile โ memory)
- Auto from task decisions (extract on completion)
- Explicit ("Remember: we use X for Y")
- Pattern detection (3x same approach โ prompt)
### R6: Confidence Decay
- Memories decay without validation
- Usage boosts confidence
- Prune below threshold
## Technical Design
### graph.json Schema
```json
{
"version": "1.0.0",
"nodes": {
"tasks": { "TASK-31": { "concepts": [...], "path": "..." } },
"concepts": { "auth": { "aliases": ["login", "OAuth"] } },
"memories": { "mem-001": { "type": "pitfall", "confidence": 0.9 } }
},
"edges": [
{"from": "TASK-31", "to": "auth", "type": "implements"},
{"from": "mem-001", "to": "TASK-12", "type": "learned-from"}
],
"concept_index": {
"auth": ["TASK-29", "mem-001", "SOP-001"]
}
}
```
### Token Budget
| Component | Tokens |
|-----------|--------|
| graph.json (50 nodes) | ~1000 |
| Memory summaries (3) | ~300 |
| **Session overhead** | **~1.3k** |
โ
Under 2k requirement
## Implementation Phases
### Phase 1: Foundation (2-3 days)
- [ ] `.agent/knowledge/` structure
- [ ] `graph.json` schema
- [ ] `graph_manager.py` (CRUD, traversal)
- [ ] `nav-graph-init` (one-time build)
### Phase 2: Core Skill (2-3 days)
- [ ] `nav-graph` skill
- [ ] Query functions
- [ ] Natural language triggers
- [ ] Response formatting
### Phase 3: Memory Layer (2-3 days)
- [ ] Correction โ memory capture
- [ ] Task decision โ memory
- [ ] Confidence decay
- [ ] Memory surfacing
### Phase 4: Integration (2-3 days)
- [ ] nav-start (load graph)
- [ ] nav-task (update graph)
- [ ] nav-profile (correction โ memory)
### Phase 5: Polish (post-6.0.0)
- [ ] Conflict detection
- [ ] Staleness pruning
- [ ] Visualization export
## Verify
```bash
# Structure exists
test -d ".agent/knowledge" && echo "โ Directory"
test -f ".agent/knowledge/graph.json" && echo "โ Index"
# Skill works
test -f "skills/nav-graph/SKILL.md" && echo "โ Skill"
# Query works
# "What do we know about auth?" โ returns related items
```
## Done
- [ ] Graph index loads on session start
- [ ] "What do we know about X?" returns unified results
- [ ] Memories auto-captured from corrections
- [ ] <1.5k token overhead
- [ ] Relationship traversal working
## Open Questions
1. **Concept extraction**: LLM-assisted or manual tagging?
โ Recommendation: Auto-extract, allow override
2. **Cross-project**: Share patterns between projects?
โ Recommendation: Project-scoped v6.0, global v6.1
3. **Memory limits**: How many before pruning?
โ Recommendation: Soft limit 100, prune <0.3 confidence
## References
- Original concept: TASK-35 (Project Memory)
- Related: nav-profile, nav-marker, nav-task
- Inspiration: Knowledge graphs, semantic search
Attribution
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