Initial: Claude config with agents, skills, commands, rules and scripts
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skills/iterative-retrieval/SKILL.md
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skills/iterative-retrieval/SKILL.md
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name: iterative-retrieval
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description: Pattern for progressively refining context retrieval to solve the subagent context problem
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---
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# Iterative Retrieval Pattern
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Solves the "context problem" in multi-agent workflows where subagents don't know what context they need until they start working.
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## When to Activate
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- Spawning subagents that need codebase context they cannot predict upfront
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- Building multi-agent workflows where context is progressively refined
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- Encountering "context too large" or "missing context" failures in agent tasks
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- Designing RAG-like retrieval pipelines for code exploration
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- Optimizing token usage in agent orchestration
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## The Problem
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Subagents are spawned with limited context. They don't know:
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- Which files contain relevant code
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- What patterns exist in the codebase
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- What terminology the project uses
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Standard approaches fail:
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- **Send everything**: Exceeds context limits
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- **Send nothing**: Agent lacks critical information
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- **Guess what's needed**: Often wrong
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## The Solution: Iterative Retrieval
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A 4-phase loop that progressively refines context:
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```
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┌─────────────────────────────────────────────┐
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│ │
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│ ┌──────────┐ ┌──────────┐ │
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│ │ DISPATCH │─────▶│ EVALUATE │ │
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│ └──────────┘ └──────────┘ │
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│ ▲ │ │
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│ │ ▼ │
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│ ┌──────────┐ ┌──────────┐ │
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│ │ LOOP │◀─────│ REFINE │ │
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│ └──────────┘ └──────────┘ │
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│ │
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│ Max 3 cycles, then proceed │
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└─────────────────────────────────────────────┘
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```
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### Phase 1: DISPATCH
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Initial broad query to gather candidate files:
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```javascript
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// Start with high-level intent
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const initialQuery = {
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patterns: ['src/**/*.ts', 'lib/**/*.ts'],
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keywords: ['authentication', 'user', 'session'],
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excludes: ['*.test.ts', '*.spec.ts']
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};
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// Dispatch to retrieval agent
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const candidates = await retrieveFiles(initialQuery);
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```
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### Phase 2: EVALUATE
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Assess retrieved content for relevance:
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```javascript
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function evaluateRelevance(files, task) {
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return files.map(file => ({
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path: file.path,
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relevance: scoreRelevance(file.content, task),
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reason: explainRelevance(file.content, task),
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missingContext: identifyGaps(file.content, task)
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}));
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}
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```
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Scoring criteria:
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- **High (0.8-1.0)**: Directly implements target functionality
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- **Medium (0.5-0.7)**: Contains related patterns or types
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- **Low (0.2-0.4)**: Tangentially related
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- **None (0-0.2)**: Not relevant, exclude
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### Phase 3: REFINE
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Update search criteria based on evaluation:
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```javascript
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function refineQuery(evaluation, previousQuery) {
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return {
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// Add new patterns discovered in high-relevance files
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patterns: [...previousQuery.patterns, ...extractPatterns(evaluation)],
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// Add terminology found in codebase
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keywords: [...previousQuery.keywords, ...extractKeywords(evaluation)],
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// Exclude confirmed irrelevant paths
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excludes: [...previousQuery.excludes, ...evaluation
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.filter(e => e.relevance < 0.2)
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.map(e => e.path)
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],
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// Target specific gaps
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focusAreas: evaluation
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.flatMap(e => e.missingContext)
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.filter(unique)
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};
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}
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```
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### Phase 4: LOOP
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Repeat with refined criteria (max 3 cycles):
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```javascript
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async function iterativeRetrieve(task, maxCycles = 3) {
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let query = createInitialQuery(task);
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let bestContext = [];
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for (let cycle = 0; cycle < maxCycles; cycle++) {
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const candidates = await retrieveFiles(query);
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const evaluation = evaluateRelevance(candidates, task);
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// Check if we have sufficient context
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const highRelevance = evaluation.filter(e => e.relevance >= 0.7);
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if (highRelevance.length >= 3 && !hasCriticalGaps(evaluation)) {
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return highRelevance;
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}
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// Refine and continue
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query = refineQuery(evaluation, query);
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bestContext = mergeContext(bestContext, highRelevance);
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}
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return bestContext;
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}
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```
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## Practical Examples
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### Example 1: Bug Fix Context
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```
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Task: "Fix the authentication token expiry bug"
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Cycle 1:
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DISPATCH: Search for "token", "auth", "expiry" in src/**
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EVALUATE: Found auth.ts (0.9), tokens.ts (0.8), user.ts (0.3)
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REFINE: Add "refresh", "jwt" keywords; exclude user.ts
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Cycle 2:
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DISPATCH: Search refined terms
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EVALUATE: Found session-manager.ts (0.95), jwt-utils.ts (0.85)
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REFINE: Sufficient context (2 high-relevance files)
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Result: auth.ts, tokens.ts, session-manager.ts, jwt-utils.ts
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```
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### Example 2: Feature Implementation
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```
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Task: "Add rate limiting to API endpoints"
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Cycle 1:
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DISPATCH: Search "rate", "limit", "api" in routes/**
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EVALUATE: No matches - codebase uses "throttle" terminology
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REFINE: Add "throttle", "middleware" keywords
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Cycle 2:
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DISPATCH: Search refined terms
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EVALUATE: Found throttle.ts (0.9), middleware/index.ts (0.7)
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REFINE: Need router patterns
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Cycle 3:
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DISPATCH: Search "router", "express" patterns
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EVALUATE: Found router-setup.ts (0.8)
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REFINE: Sufficient context
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Result: throttle.ts, middleware/index.ts, router-setup.ts
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```
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## Integration with Agents
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Use in agent prompts:
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```markdown
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When retrieving context for this task:
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1. Start with broad keyword search
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2. Evaluate each file's relevance (0-1 scale)
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3. Identify what context is still missing
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4. Refine search criteria and repeat (max 3 cycles)
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5. Return files with relevance >= 0.7
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```
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## Best Practices
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1. **Start broad, narrow progressively** - Don't over-specify initial queries
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2. **Learn codebase terminology** - First cycle often reveals naming conventions
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3. **Track what's missing** - Explicit gap identification drives refinement
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4. **Stop at "good enough"** - 3 high-relevance files beats 10 mediocre ones
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5. **Exclude confidently** - Low-relevance files won't become relevant
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## Related
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- [The Longform Guide](https://x.com/affaanmustafa/status/2014040193557471352) - Subagent orchestration section
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- `continuous-learning` skill - For patterns that improve over time
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- Agent definitions in `~/.claude/agents/`
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