Como usar
- Copie o comando e verifique o pacote antes de instalar no seu ambiente de agente.
- Consulte no original as ferramentas, credenciais e ambientes necessários.
- Descreva os dados de entrada e a entrega esperada; confira a saída com as fontes.
npx skills add https://github.com/affaan-m/ecc --skill iterative-retrievalAntes de começar
- A instalação não inclui assinatura de modelo, franquia API ou acesso aos seus arquivos.
- Estrelas e instalações indicam atividade, não um teste independente de qualidade ou segurança.
Documento original do Skill
Renderizado do repositório de origem, preservando títulos, exemplos, código, tabelas, links e imagens.
Iterative Retrieval Pattern
Solves the "context problem" in multi-agent workflows where subagents don't know what context they need until they start working.
When to Activate
- Spawning subagents that need codebase context they cannot predict upfront
- Building multi-agent workflows where context is progressively refined
- Encountering "context too large" or "missing context" failures in agent tasks
- Designing RAG-like retrieval pipelines for code exploration
- Optimizing token usage in agent orchestration
The Problem
Subagents are spawned with limited context. They don't know:
- Which files contain relevant code
- What patterns exist in the codebase
- What terminology the project uses
Standard approaches fail:
- Send everything: Exceeds context limits
- Send nothing: Agent lacks critical information
- Guess what's needed: Often wrong
The Solution: Iterative Retrieval
A 4-phase loop that progressively refines context:
┌─────────────────────────────────────────────┐
│ │
│ ┌──────────┐ ┌──────────┐ │
│ │ DISPATCH │─────│ EVALUATE │ │
│ └──────────┘ └──────────┘ │
│ ▲ │ │
│ │ ▼ │
│ ┌──────────┐ ┌──────────┐ │
│ │ LOOP │─────│ REFINE │ │
│ └──────────┘ └──────────┘ │
│ │
│ Max 3 cycles, then proceed │
└─────────────────────────────────────────────┘Phase 1: DISPATCH
Initial broad query to gather candidate files:
javascript
// Start with high-level intent
const initialQuery = {
patterns: ['src/**/*.ts', 'lib/**/*.ts'],
keywords: ['authentication', 'user', 'session'],
excludes: ['*.test.ts', '*.spec.ts']
};
// Dispatch to retrieval agent
const candidates = await retrieveFiles(initialQuery);Phase 2: EVALUATE
Assess retrieved content for relevance:
javascript
function evaluateRelevance(files, task) {
return files.map(file => ({
path: file.path,
relevance: scoreRelevance(file.content, task),
reason: explainRelevance(file.content, task),
missingContext: identifyGaps(file.content, task)
}));
}Scoring criteria:
- High (0.8-1.0): Directly implements target functionality
- Medium (0.5-0.7): Contains related patterns or types
- Low (0.2-0.4): Tangentially related
- None (0-0.2): Not relevant, exclude
Phase 3: REFINE
Update search criteria based on evaluation:
javascript
function refineQuery(evaluation, previousQuery) {
return {
// Add new patterns discovered in high-relevance files
patterns: [...previousQuery.patterns, ...extractPatterns(evaluation)],
// Add terminology found in codebase
keywords: [...previousQuery.keywords, ...extractKeywords(evaluation)],
// Exclude confirmed irrelevant paths
excludes: [...previousQuery.excludes, ...evaluation
.filter(e => e.relevance < 0.2)
.map(e => e.path)
],
// Target specific gaps
focusAreas: evaluation
.flatMap(e => e.missingContext)
.filter(unique)
};
}Phase 4: LOOP
Repeat with refined criteria (max 3 cycles):
javascript
async function iterativeRetrieve(task, maxCycles = 3) {
let query = createInitialQuery(task);
let bestContext = [];
for (let cycle = 0; cycle < maxCycles; cycle++) {
const candidates = await retrieveFiles(query);
const evaluation = evaluateRelevance(candidates, task);
// Check if we have sufficient context
const highRelevance = evaluation.filter(e => e.relevance >= 0.7);
if (highRelevance.length >= 3 && !hasCriticalGaps(evaluation)) {
return highRelevance;
}
// Refine and continue
query = refineQuery(evaluation, query);
bestContext = mergeContext(bestContext, highRelevance);
}
return bestContext;
}Practical Examples
Example 1: Bug Fix Context
Task: "Fix the authentication token expiry bug"
Cycle 1:
DISPATCH: Search for "token", "auth", "expiry" in src/**
EVALUATE: Found auth.ts (0.9), tokens.ts (0.8), user.ts (0.3)
REFINE: Add "refresh", "jwt" keywords; exclude user.ts
Cycle 2:
DISPATCH: Search refined terms
EVALUATE: Found session-manager.ts (0.95), jwt-utils.ts (0.85)
REFINE: Sufficient context (2 high-relevance files)
Result: auth.ts, tokens.ts, session-manager.ts, jwt-utils.tsExample 2: Feature Implementation
Task: "Add rate limiting to API endpoints"
Cycle 1:
DISPATCH: Search "rate", "limit", "api" in routes/**
EVALUATE: No matches - codebase uses "throttle" terminology
REFINE: Add "throttle", "middleware" keywords
Cycle 2:
DISPATCH: Search refined terms
EVALUATE: Found throttle.ts (0.9), middleware/index.ts (0.7)
REFINE: Need router patterns
Cycle 3:
DISPATCH: Search "router", "express" patterns
EVALUATE: Found router-setup.ts (0.8)
REFINE: Sufficient context
Result: throttle.ts, middleware/index.ts, router-setup.tsIntegration with Agents
Use in agent prompts:
markdown
When retrieving context for this task:
1. Start with broad keyword search
2. Evaluate each file's relevance (0-1 scale)
3. Identify what context is still missing
4. Refine search criteria and repeat (max 3 cycles)
5. Return files with relevance >= 0.7Best Practices
- Start broad, narrow progressively - Don't over-specify initial queries
- Learn codebase terminology - First cycle often reveals naming conventions
- Track what's missing - Explicit gap identification drives refinement
- Stop at "good enough" - 3 high-relevance files beats 10 mediocre ones
- Exclude confidently - Low-relevance files won't become relevant
Related
- The Longform Guide - Subagent orchestration section
continuous-learningskill - For patterns that improve over time- Agent definitions bundled with ECC (manual install path:
agents/)
