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iterative-retrieval

逐步优化上下文检索以解决子代理上下文问题的模式

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This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.

Stars
86,091
Hot score
99
Updated
March 20, 2026
Overall rating
C5.0
Composite score
5.0
Best-practice grade
B75.1

Install command

npx @skill-hub/cli install affaan-m-everything-claude-code-iterative-retrieval

Repository

affaan-m/everything-claude-code

Skill path: docs/zh-CN/skills/iterative-retrieval

逐步优化上下文检索以解决子代理上下文问题的模式

Open repository

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Primary workflow: Ship Full Stack.

Technical facets: Full Stack.

Target audience: everyone.

License: Unknown.

Original source

Catalog source: SkillHub Club.

Repository owner: affaan-m.

This is still a mirrored public skill entry. Review the repository before installing into production workflows.

What it helps with

  • Install iterative-retrieval into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
  • Review https://github.com/affaan-m/everything-claude-code before adding iterative-retrieval to shared team environments
  • Use iterative-retrieval for development workflows

Works across

Claude CodeCodex CLIGemini CLIOpenCode

Favorites: 0.

Sub-skills: 0.

Aggregator: No.

Original source / Raw SKILL.md

---
name: iterative-retrieval
description: 逐步优化上下文检索以解决子代理上下文问题的模式
origin: ECC
---

# 迭代检索模式

解决多智能体工作流中的“上下文问题”,即子智能体在开始工作前不知道需要哪些上下文。

## 何时激活

* 当需要生成需要代码库上下文但无法预先预测的子代理时
* 构建需要逐步完善上下文的多代理工作流时
* 在代理任务中遇到"上下文过大"或"缺少上下文"的失败时
* 为代码探索设计类似 RAG 的检索管道时
* 在代理编排中优化令牌使用时

## 问题

子智能体被生成时上下文有限。它们不知道:

* 哪些文件包含相关代码
* 代码库中存在哪些模式
* 项目使用什么术语

标准方法会失败:

* **发送所有内容**:超出上下文限制
* **不发送任何内容**:智能体缺乏关键信息
* **猜测所需内容**:经常出错

## 解决方案:迭代检索

一个逐步优化上下文的 4 阶段循环:

```
┌─────────────────────────────────────────────┐
│                                             │
│   ┌──────────┐      ┌──────────┐            │
│   │ DISPATCH │─────▶│ EVALUATE │            │
│   └──────────┘      └──────────┘            │
│        ▲                  │                 │
│        │                  ▼                 │
│   ┌──────────┐      ┌──────────┐            │
│   │   LOOP   │◀─────│  REFINE  │            │
│   └──────────┘      └──────────┘            │
│                                             │
│        Max 3 cycles, then proceed           │
└─────────────────────────────────────────────┘
```

### 阶段 1:调度

初始的广泛查询以收集候选文件:

```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);
```

### 阶段 2:评估

评估检索到的内容的相关性:

```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)
  }));
}
```

评分标准:

* **高 (0.8-1.0)**:直接实现目标功能
* **中 (0.5-0.7)**:包含相关模式或类型
* **低 (0.2-0.4)**:略微相关
* **无 (0-0.2)**:不相关,排除

### 阶段 3:优化

根据评估结果更新搜索条件:

```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)
  };
}
```

### 阶段 4:循环

使用优化后的条件重复(最多 3 个周期):

```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;
}
```

## 实际示例

### 示例 1:错误修复上下文

```
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
```

### 示例 2:功能实现

```
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
```

## 与智能体集成

在智能体提示中使用:

```markdown
在为该任务检索上下文时:
1. 从广泛的关键词搜索开始
2. 评估每个文件的相关性(0-1 分制)
3. 识别仍缺失哪些上下文
4. 优化搜索条件并重复(最多 3 个循环)
5. 返回相关性 >= 0.7 的文件

```

## 最佳实践

1. **先宽泛,后逐步细化** - 不要过度指定初始查询
2. **学习代码库术语** - 第一轮循环通常能揭示命名约定
3. **跟踪缺失内容** - 明确识别差距以驱动优化
4. **在“足够好”时停止** - 3 个高相关性文件胜过 10 个中等相关性文件
5. **自信地排除** - 低相关性文件不会变得相关

## 相关

* [长篇指南](https://x.com/affaanmustafa/status/2014040193557471352) - 子智能体编排部分
* `continuous-learning` 技能 - 用于随时间改进的模式
* 在 `~/.claude/agents/` 中的智能体定义
iterative-retrieval | SkillHub