Best fit
- 서브에이전트 컨텍스트 문제를 해결하기 위한 점진적 컨텍스트 검색 개선 패턴
affaan-m/ECC
서브에이전트 컨텍스트 문제를 해결하기 위한 점진적 컨텍스트 검색 개선 패턴
npx skills add https://github.com/affaan-m/ECC --skill "docs/ko-KR/skills/iterative-retrieval"Source checked Jul 28, 2026·Refresh due Oct 26, 2026
Reorganized from the pinned upstream SKILL.md
According to the pinned SKILL.md from affaan-m/ECC: 서브에이전트가 작업을 시작하기 전까지 필요한 컨텍스트를 알 수 없는 멀티 에이전트 워크플로우의 "컨텍스트 문제"를 해결합니다.
npx skills add https://github.com/affaan-m/ECC --skill "docs/ko-KR/skills/iterative-retrieval"Best fit
Bring this context
Expected outputs
Key source sections
Sections are extracted automatically from the pinned SKILL.md and link back to the source.
사전에 예측할 수 없는 코드베이스 컨텍스트가 필요한 서브에이전트를 생성할 때
서브에이전트는 제한된 컨텍스트로 생성됩니다. 다음을 알 수 없습니다: - 관련 코드가 포함된 파일 - 코드베이스에 존재하는 패턴 - 프로젝트에서 사용하는 용어
컨텍스트를 점진적으로 개선하는 4단계 루프:
후보 파일을 수집하기 위한 초기 광범위 쿼리:
점수 기준: - 높음 (0.8-1.0): 대상 기능을 직접 구현 - 중간 (0.5-0.7): 관련 패턴이나 타입을 포함 - 낮음 (0.2-0.4): 간접적으로 관련 - 없음 (0-0.2): 관련 없음, 제외
SkillSignal prompt templates
These prompts were written by SkillSignal from the source structure; they are not upstream text.
Task-start prompt
Confirm source fit, inputs, and outputs before acting.
Use iterative-retrieval to help me with: [specific task]. Context: [files, data, or background]. Constraints: [environment, scope, and prohibited actions]. Before acting, check the pinned SKILL.md and explain which sections apply, what inputs are still missing, and what you will deliver.
Source-guided execution
Make the Agent explicitly follow the key extracted sections.
Apply the pinned iterative-retrieval source to [task]. Pay particular attention to these source sections: “활성화 시점”, “문제”, “해결책: 반복적 검색”, “1단계: DISPATCH”, “2단계: EVALUATE”. Preserve the important decision at each step. Mark facts not covered by the source as “needs confirmation” instead of inventing them. Then verify the result against my acceptance criteria: [criteria].
Result-review prompt
Check omissions, permissions, and source drift before delivery.
Review the current iterative-retrieval result: (1) does it satisfy the original task; (2) were any applicable steps or limits in the pinned SKILL.md missed; (3) did it perform any unauthorized file, command, network, or data action; and (4) which conclusions remain unverified? List issues first, then fix only what the source or user authorization supports.
Output checklist
The task matches the purpose documented in the SKILL.md.
The source section “활성화 시점” has been checked.
The source section “문제” has been checked.
The source section “해결책: 반복적 검색” has been checked.
The source section “1단계: DISPATCH” has been checked.
Inputs, constraints, and acceptance criteria are explicit.
Unverified facts, compatibility, and outcome claims are clearly marked.
Any file, command, network, or data action has been reviewed.
Choose a different workflow
Pattern for progressively refining context retrieval to solve the subagent context problem
A separate implementation from affaan-m/ECC; compare its source, maintenance signals, and permission requirements.
Open source detailPattern for progressively refining context retrieval to solve the subagent context problem
A separate implementation from affaan-m/ECC; compare its source, maintenance signals, and permission requirements.
Open source detailサブエージェントのコンテキスト問題を解決するために、コンテキスト取得を段階的に洗練するパターン
A separate implementation from affaan-m/ECC; compare its source, maintenance signals, and permission requirements.
Open source detailFAQ
서브에이전트가 작업을 시작하기 전까지 필요한 컨텍스트를 알 수 없는 멀티 에이전트 워크플로우의 "컨텍스트 문제"를 해결합니다.
The catalog detected this source-specific install command: npx skills add https://github.com/affaan-m/ECC --skill "docs/ko-KR/skills/iterative-retrieval". Inspect the command and pinned source before running it.
No dedicated Agent platform is declared in the pinned source record.
Quality breakdown
Based on traceable docs and repository signals; stars are not treated as quality.
Compare before choosing
These links are selected from shared tasks, functions, stacks, platforms, and same-name variants. Compare the source owner, documentation, permissions, and maintenance signals.
Pattern for progressively refining context retrieval to solve the subagent context problem
Pattern for progressively refining context retrieval to solve the subagent context problem
サブエージェントのコンテキスト問題を解決するために、コンテキスト取得を段階的に洗練するパターン
逐步优化上下文检索以解决子代理上下文问题的模式
When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this," "which version is better," "test two versions," "statistical significance," "how long should I run this test," "growth experiments," "experiment velocity," "experiment backlog," "ICE score," "experimentation program
서브에이전트가 작업을 시작하기 전까지 필요한 컨텍스트를 알 수 없는 멀티 에이전트 워크플로우의 "컨텍스트 문제"를 해결합니다.
서브에이전트는 제한된 컨텍스트로 생성됩니다. 다음을 알 수 없습니다:
표준 접근법의 실패:
컨텍스트를 점진적으로 개선하는 4단계 루프:
┌─────────────────────────────────────────────┐
│ │
│ ┌──────────┐ ┌──────────┐ │
│ │ DISPATCH │─────│ EVALUATE │ │
│ └──────────┘ └──────────┘ │
│ ▲ │ │
│ │ ▼ │
│ ┌──────────┐ ┌──────────┐ │
│ │ LOOP │─────│ REFINE │ │
│ └──────────┘ └──────────┘ │
│ │
│ Max 3 cycles, then proceed │
└─────────────────────────────────────────────┘
후보 파일을 수집하기 위한 초기 광범위 쿼리:
// 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);
검색된 콘텐츠의 관련성 평가:
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)
}));
}
점수 기준:
평가를 기반으로 검색 기준 업데이트:
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)
};
}
개선된 기준으로 반복 (최대 3회):
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;
}
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.ts
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.ts
에이전트 프롬프트에서 사용:
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 >= 0.7
continuous-learning 스킬 - 시간이 지남에 따라 개선되는 패턴~/.claude/agents/의 에이전트 정의