Knowledge
Merged Skills
- •context-management: Project knowledge graph, entity lookup
- •caching: Hot cache, domain index, gotchas lookup
⚠️ Critical Gotchas
| Category | Pattern | Solution |
|---|---|---|
| Multiple queries | Running --query 5 times | Read first 100 lines ONCE at START |
| Repeated reads | Reading knowledge file multiple times | Keep in memory for entire session |
| Wrong lookup | Searching when data is cached | Check hot_cache before file reads |
| Stale knowledge | Entity refs outdated | Run knowledge.py --update after sessions |
| Missing gotchas | New issues not documented | Add to workflow log, will be merged |
Rules
| Rule | Pattern |
|---|---|
| Load once | Read first 100 lines ONCE at session start |
| Memory-first | Keep loaded knowledge in context |
| Hot cache first | Check hot_cache.entity_refs before file reads |
| Gotchas first | Check gotchas.issues when debugging |
| Update at END | Run knowledge.py --update in END phase |
Avoid
| ❌ Bad | ✅ Good |
|---|---|
| Run --query 5 times | Read first 100 lines once |
| grep knowledge.json | Check loaded gotchas in memory |
| list_dir for paths | Check domain_index |
| Search for entity | Check hot_cache first |
⛔ MANDATORY: Load Once at START
bash
head -100 project_knowledge.json # Do this ONCE
This gives you (in memory for entire session):
| Line | Content | Use For |
|---|---|---|
| 1 | HOT_CACHE | Top 20 entities + file paths |
| 2 | DOMAIN_INDEX | 81 backend, 71 frontend paths |
| 3 | CHANGE_TRACKING | File modification hashes |
| 4 | GOTCHAS | 38 known issues + solutions |
| 5 | INTERCONNECTIONS | Entity chains |
| 6 | SESSION_PATTERNS | Preload hints |
| 7-12 | Layer entities | Graph structure |
| 13-93 | Layer relations | Lookup paths |
Patterns
bash
# Pattern 1: Session start - load knowledge head -100 project_knowledge.json # Pattern 2: Query specific entity (rare, only if cache miss) python .github/scripts/knowledge.py --query "entity_name" # Pattern 3: Update knowledge after session python .github/scripts/knowledge.py --update
python
# Pattern 4: Using knowledge programmatically
import json
with open('project_knowledge.json') as f:
for i, line in enumerate(f):
if i >= 100:
break
data = json.loads(line)
if data.get('type') == 'hot_cache':
entity_refs = data['entity_refs']
elif data.get('type') == 'gotchas':
issues = data['issues']
Query Order (Using In-Memory Knowledge)
| Step | Check | If Miss |
|---|---|---|
| 1 | hot_cache.top_entities | → Step 2 |
| 2 | gotchas.issues | → Step 3 |
| 3 | domain_index.backend/frontend | → Step 4 |
| 4 | layer relations | → Step 5 |
| 5 | Use --query CLI | → Step 6 |
| 6 | Read file directly | Last resort |
File Structure
| Lines | Content |
|---|---|
| 1-6 | Headers (ALL lookup data) |
| 7-12 | Layer entities (KNOWLEDGE_GRAPH, HOT_CACHE, ...) |
| 13-93 | Layer relations (caches → entity, indexes → file) |
| 94+ | Code entities (sorted by weight) |
| 300+ | Code relations (imports, calls) |
Commands
| Task | Command |
|---|---|
| Load knowledge | head -100 project_knowledge.json |
| Query entity | python .github/scripts/knowledge.py --query "name" |
| Update knowledge | python .github/scripts/knowledge.py --update |
| Suggest updates | python .github/scripts/knowledge.py --suggest |
Stats (v4.2)
- •First 100 lines: ~15KB (fits in context)
- •Contains: 100% of lookup data
- •File reads saved: 76.8%
- •Queries saved: 90%+ (vs multiple --query calls)