/knowledge-manager
Loads relevant patterns and known errors before track planning. Searches conductor/knowledge/ for solutions we've used before and errors we've encountered. Injects findings into the planner prompt to prevent reinventing solutions and repeating mistakes. Triggered automatically
$ npx -y skills add Ibrahim-3d/orchestrator-supaconductor --skill knowledge-manager --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
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/knowledge-manager
Context preview
The summary Claude sees to decide when to auto-load this skill.
Loads relevant patterns and known errors before track planning. Searches conductor/knowledge/ for solutions we've used before and errors we've encountered. Injects findings into the planner prompt to prevent reinventing solutions and repeating mistakes. Triggered automatically
SKILL.md
knowledge-manager.SKILL.mdname: knowledge-manager
description: "Loads relevant patterns and known errors before track planning. Searches conductor/knowledge/ for solutions we've used before and errors we've encountered. Injects findings into the planner prompt to prevent reinventing solutions and repeating mistakes. Triggered automatically by orchestrator before PLAN step."
Knowledge Manager — Pre-Planning Intelligence
Searches the knowledge base for relevant patterns and errors before a track begins, injecting institutional memory into the planning process.
When This Runs
**Automatically** — The orchestrator calls this agent BEFORE dispatching the `loop-planner` for any track.
Inputs
1. **Track spec.md** — To understand what the track is about 2. **Track type** — From metadata.json (feature, UI, integration, etc.) 3. **Keywords** — Extracted from spec (e.g., "auth", "Supabase", "form", "state")
Workflow
1. Extract Keywords from Spec
read_file the track's `spec.md` and extract relevant keywords:
const keywords = extractKeywords(spec);
// Example: ["authentication", "Supabase", "login", "signup", "OAuth"]
Keywords come from:
- Section headings
- Technical terms
- Integration names (Supabase, Stripe, Gemini)
- Component types (form, modal, grid, etc.)
- Pattern names (state management, API routes, etc.)
2. Search Pattern Library
Search `conductor/knowledge/patterns.md` for matching patterns. Score each entry by keyword overlap and **return only the top 3 highest-scoring results** (skip zero-score entries):
## Relevant Patterns Found (top 3 by relevance)
### Pattern: Supabase Client Singleton
**Category**: Integration
**Relevance score**: 3/5 keywords matched
**Summary**: Use singleton pattern with server/client separation
**Key Code**:
```tsx
// lib/supabase/server.ts
export const createClient = async () => { /* ... */ };Pattern: Server Actions with Error Handling
**Category**: API **Relevance score**: 2/5 keywords matched **Summary**: Wrap all server actions with try/catch and typed responses
### 3. Search Error Registry
Search `conductor/knowledge/errors.json` for errors related to this track type. Score each entry by keyword overlap and **return only the top 3 highest-scoring results**:
```markdown
## Known Errors to Watch For
### Error: Hydration Mismatch (err-003)
**Pattern**: "Hydration failed because the initial UI does not match"
**Context**: Auth state can differ between server and client
**Prevention**: Wrap auth-dependent UI in useEffect or client component
### Error: NEXT_REDIRECT in try/catch (err-004)
**Pattern**: "NEXT_REDIRECT"
**Context**: Server actions with redirect after login
**Prevention**: Re-throw NEXT_REDIRECT errors or move redirect outside try/catch
4. Generate Knowledge Brief
Output a knowledge brief that gets injected into the planner's prompt. **Total output must not exceed 500 tokens.** If the top-3 patterns + top-3 errors would exceed this budget, truncate lower-scored entries first:
# Knowledge Brief for [Track ID]
## Relevant Patterns (Apply These)
1. **Supabase Client Singleton** — Use separate server/client clients
2. **Server Actions with Error Handling** — Typed responses with try/catch
## Known Errors (Avoid These)
1. **Hydration Mismatch** — Don't render auth-dependent UI on server
2. **NEXT_REDIRECT** — Handle redirect() specially in try/catch
## Previous Similar Work
- Track `auth-flow_20260115` implemented similar auth flow
- See `conductor/tracks/auth-flow_20260115/plan.md` for reference
## Recommendations
- Consider using the existing auth patterns from previous track
- Watch for SSR/client hydration issues with auth state
Output Format
The Knowledge Manager returns a structured brief:
{
"patterns_found": [
{
"name": "Supabase Client Singleton",
"category": "Integration",
"relevance": "high",
"summary": "...",
"code_snippet": "..."
}
],
"errors_to_watch": [
{
"id": "err-003",
"pattern": "Hydration mismatch",
"prevention": "..."
}
],
"similar_tracks": [
{
"track_id": "auth-flow_20260115",
"relevance": "Implemented OAuth flow"
}
],
"recommendations": [
"Reuse auth patterns from previous track",
"Watch for hydration issues"
]
}Integration with Orchestrator
The orchestrator injects this brief into the planner's dispatch:
// In conductor-orchestrator
async function dispatchPlanner(trackId: string) {
// 1. Run Knowledge Manager first
const knowledgeBrief = await Task({
subagent_type: "general-purpose",
description: "Load knowledge for track",
prompt: `You are the knowledge-manager agent.
Track: ${trackId}
Spec: ${specContent}
Search conductor/knowledge/patterns.md and errors.json.
Return a knowledge brief with relevant patterns and errors.`
});
// 2. Dispatch planner WITH knowledge brief
await Task({
subagent_type: "general-purpose",
description: "Create track plan",
prompt: `You are the loop-planner agent.
${knowledgeBrief.output}
Create plan.md using the patterns above where applicable.
Avoid the known errors listed.`
});
}Search Strategies
By Category
Match track type to pattern/error categories:
- UI track → Search "UI", "component", "styling" patterns
- Integration track → Search "Integration", "API", "Supabase", "Stripe" patterns
- Feature track → Search "State", "API", "Testing" patterns
By Keyword
Fuzzy match keywords from spec against pattern descriptions and error contexts.
By Recency
Prioritize patterns from recent tracks (more likely to be relevant to current codebase state).
Maintaining the Knowledge Base
The Knowledge Manager is read_file-only. Writing to the knowledge base is done by:
- **Retrospective Agent** — After track completion
- **Fixer Agent** — When discovering new error pat
Read more
name: knowledge-manager description: "Loads relevant patterns and known errors before track planning. Searches conductor/knowledge/ for solutions we've used before and errors we've encountered. Injects findings into the planner prompt to prevent reinventing solutions and repeating mistakes. Triggered automatically by orchestrator before PLAN step."
Knowledge Manager — Pre-Planning Intelligence
Searches the knowledge base for relevant patterns and errors before a track begins, injecting institutional memory into the planning process.
When This Runs
**Automatically** — The orchestrator calls this agent BEFORE dispatching the `loop-planner` for any track.
Inputs
1. **Track spec.md** — To understand what the track is about 2. **Track type** — From metadata.json (feature, UI, integration, etc.) 3. **Keywords** — Extracted from spec (e.g., "auth", "Supabase", "form", "state")
Workflow
1. Extract Keywords from Spec
read_file the track's `spec.md` and extract relevant keywords:
const keywords = extractKeywords(spec); // Example: ["authentication", "Supabase", "login", "signup", "OAuth"]
Keywords come from:
- Section headings
- Technical terms
- Integration names (Supabase, Stripe, Gemini)
- Component types (form, modal, grid, etc.)
- Pattern names (state management, API routes, etc.)
2. Search Pattern Library
Search `conductor/knowledge/patterns.md` for matching patterns. Score each entry by keyword overlap and **return only the top 3 highest-scoring results** (skip zero-score entries):
## Relevant Patterns Found (top 3 by relevance)
### Pattern: Supabase Client Singleton
**Category**: Integration
**Relevance score**: 3/5 keywords matched
**Summary**: Use singleton pattern with server/client separation
**Key Code**:
```tsx
// lib/supabase/server.ts
export const createClient = async () => { /* ... */ };Pattern: Server Actions with Error Handling
**Category**: API **Relevance score**: 2/5 keywords matched **Summary**: Wrap all server actions with try/catch and typed responses
### 3. Search Error Registry Search `conductor/knowledge/errors.json` for errors related to this track type. Score each entry by keyword overlap and **return only the top 3 highest-scoring results**: ```markdown ## Known Errors to Watch For ### Error: Hydration Mismatch (err-003) **Pattern**: "Hydration failed because the initial UI does not match" **Context**: Auth state can differ between server and client **Prevention**: Wrap auth-dependent UI in useEffect or client component ### Error: NEXT_REDIRECT in try/catch (err-004) **Pattern**: "NEXT_REDIRECT" **Context**: Server actions with redirect after login **Prevention**: Re-throw NEXT_REDIRECT errors or move redirect outside try/catch
4. Generate Knowledge Brief
Output a knowledge brief that gets injected into the planner's prompt. **Total output must not exceed 500 tokens.** If the top-3 patterns + top-3 errors would exceed this budget, truncate lower-scored entries first:
# Knowledge Brief for [Track ID] ## Relevant Patterns (Apply These) 1. **Supabase Client Singleton** — Use separate server/client clients 2. **Server Actions with Error Handling** — Typed responses with try/catch ## Known Errors (Avoid These) 1. **Hydration Mismatch** — Don't render auth-dependent UI on server 2. **NEXT_REDIRECT** — Handle redirect() specially in try/catch ## Previous Similar Work - Track `auth-flow_20260115` implemented similar auth flow - See `conductor/tracks/auth-flow_20260115/plan.md` for reference ## Recommendations - Consider using the existing auth patterns from previous track - Watch for SSR/client hydration issues with auth state
Output Format
The Knowledge Manager returns a structured brief:
{
"patterns_found": [
{
"name": "Supabase Client Singleton",
"category": "Integration",
"relevance": "high",
"summary": "...",
"code_snippet": "..."
}
],
"errors_to_watch": [
{
"id": "err-003",
"pattern": "Hydration mismatch",
"prevention": "..."
}
],
"similar_tracks": [
{
"track_id": "auth-flow_20260115",
"relevance": "Implemented OAuth flow"
}
],
"recommendations": [
"Reuse auth patterns from previous track",
"Watch for hydration issues"
]
}Integration with Orchestrator
The orchestrator injects this brief into the planner's dispatch:
// In conductor-orchestrator
async function dispatchPlanner(trackId: string) {
// 1. Run Knowledge Manager first
const knowledgeBrief = await Task({
subagent_type: "general-purpose",
description: "Load knowledge for track",
prompt: `You are the knowledge-manager agent.
Track: ${trackId}
Spec: ${specContent}
Search conductor/knowledge/patterns.md and errors.json.
Return a knowledge brief with relevant patterns and errors.`
});
// 2. Dispatch planner WITH knowledge brief
await Task({
subagent_type: "general-purpose",
description: "Create track plan",
prompt: `You are the loop-planner agent.
${knowledgeBrief.output}
Create plan.md using the patterns above where applicable.
Avoid the known errors listed.`
});
}Search Strategies
By Category
Match track type to pattern/error categories:
- UI track → Search "UI", "component", "styling" patterns
- Integration track → Search "Integration", "API", "Supabase", "Stripe" patterns
- Feature track → Search "State", "API", "Testing" patterns
By Keyword
Fuzzy match keywords from spec against pattern descriptions and error contexts.
By Recency
Prioritize patterns from recent tracks (more likely to be relevant to current codebase state).
Maintaining the Knowledge Base
The Knowledge Manager is read_file-only. Writing to the knowledge base is done by:
- **Retrospective Agent** — After track completion
- **Fixer Agent** — When discovering new error pat
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