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Agent Skill · 研究检索

drift-analysis(漂移分析)

drift-analysis 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

drift-analysis 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 71,089。

总安装 196周安装 8GitHub Stars 748下载 63核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:drift-analysis(漂移分析)
来源仓库:https://github.com/agent-sh/agentsys
仓库路径:skills/drift-analysis
安装命令:
npx skills add https://github.com/agent-sh/agentsys --skill drift-analysis
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/agent-sh/agentsys --skill drift-analysis

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

检测项目状态漂移,识别计划与实现之间的偏差并提出修复建议。适用于维护大型项目一致性、追踪文档与代码同步情况的场景。基于纯 JavaScript 收集器扫描仓库、文档与代码库,语义分析由 Opus 模型完成。输出包含证据指针与重构优先级,但需人工确认关键决策合理性。

依赖 repo-intel 或 grep 定位入口点,对非支持语言(如 PHP)可能失效。

来源仓库内路径:skills/drift-analysis

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/agent-sh/agentsys --skill drift-analysis;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

drift-analysis 怎么安装?

在终端执行 npx skills add https://github.com/agent-sh/agentsys --skill drift-analysis。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

drift-analysis 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

drift-analysis 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

drift-analysis 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

drift-analysis 用的人多吗?

公开数据是累计安装 196 次,近一周安装 8 次,下载 63 次,GitHub 748 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

drift-analysis 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
drift-analysis

漂移分析 · 本页

196748需要联网未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Drift Analysis

Knowledge and patterns for analyzing project state, detecting plan drift, and creating prioritized reconstruction plans.

Architecture Overview

/drift-detect
        │
        ├─→ collectors.js (pure JavaScript)
        │   ├─ scanGitHubState()
        │   ├─ analyzeDocumentation()
        │   └─ scanCodebase()
        │
        └─→ plan-synthesizer (Opus)
            └─ Deep semantic analysis with full context

Data collection: Pure JavaScript (no LLM overhead) Semantic analysis: Single Opus call with complete context

Drift Detection Patterns

Types of Drift

Plan Drift: When documented plans diverge from actual implementation

  • PLAN.md items remain unchecked for extended periods
  • Roadmap milestones slip without updates
  • Sprint/phase goals not reflected in code changes

Documentation Drift: When documentation falls behind implementation

  • New features exist without corresponding docs
  • README describes features that don't exist
  • API docs don't match actual endpoints

Issue Drift: When issue tracking diverges from reality

  • Stale issues that no longer apply
  • Completed work without closed issues
  • High-priority items neglected

Scope Drift: When project scope expands beyond original plans

  • More features documented than can be delivered
  • Continuous addition without completion
  • Ever-growing backlog with no pruning

Detection Signals

HIGH-CONFIDENCE DRIFT INDICATORS:
- Milestone 30+ days overdue with open issues
- PLAN.md < 30% completion after 90 days
- 5+ high-priority issues stale > 60 days
- README features not found in codebase

MEDIUM-CONFIDENCE INDICATORS:
- Documentation files unchanged for 180+ days
- Draft PRs open > 30 days
- Issue themes don't match code activity
- Large gap between documented and implemented features

LOW-CONFIDENCE INDICATORS:
- Many TODOs in codebase
- Stale dependencies
- Old git branches not merged

Prioritization Framework

Priority Calculation

function calculatePriority(item, weights) {
  let score = 0;

  // Severity base score
  const severityScores = {
    critical: 15,
    high: 10,
    medium: 5,
    low: 2
  };
  score += severityScores[item.severity] || 5;

  // Category multiplier
  const categoryWeights = {
    security: 2.0,    // Security issues get 2x
    bugs: 1.5,        // Bugs get 1.5x
    infrastructure: 1.3,
    features: 1.0,
    documentation: 0.8
  };
  score *= categoryWeights[item.category] || 1.0;

  // Recency boost
  if (item.createdRecently) score *= 1.2;

  // Stale penalty (old items slightly deprioritized)
  if (item.daysStale > 180) score *= 0.9;

  return Math.round(score);
}

Time Bucket Thresholds

BucketCriteriaMax Items
Immediateseverity=critical OR priority >= 155
Short-termseverity=high OR priority >= 1010
Medium-termpriority >= 515
Backlogeverything else20

Priority Weights (Default)

security: 10     # Security issues always top priority
bugs: 8          # Bugs affect users directly
features: 5      # New functionality
documentation: 3 # Important but not urgent
tech-debt: 4     # Keeps codebase healthy

Cross-Reference Patterns

Document-to-Code Matching

// Fuzzy matching for feature names
function featureMatch(docFeature, codeFeature) {
  const normalize = s => s
    .toLowerCase()
    .replace(/[-_\s]+/g, '')
    .replace(/s$/, ''); // Remove trailing 's'

  const docNorm = normalize(docFeature);
  const codeNorm = normalize(codeFeature);

  return docNorm.includes(codeNorm) ||
         codeNorm.includes(docNorm) ||
         levenshteinDistance(docNorm, codeNorm) < 3;
}

Common Mismatches

Documented AsImplemented As
"user authentication"auth/, login/, session/
"API endpoints"routes/, api/, handlers/
"database models"models/, entities/, schemas/
"caching layer"cache/, redis/, memcache/
"logging system"logger/, logs/, telemetry/

Output Templates

Drift Report Section

## Drift Analysis

### {drift_type}
**Severity**: {severity}
**Detected In**: {source}

{description}

**Evidence**:
{evidence_items}

**Recommendation**: {recommendation}

Gap Report Section

## Gap: {gap_title}

**Category**: {category}
**Severity**: {severity}

{description}

**Impact**: {impact_description}

**To Address**:
1. {action_item_1}
2. {action_item_2}

Reconstruction Plan Section

## Reconstruction Plan

### Immediate Actions (This Week)
{immediate_items_numbered}

### Short-Term (This Month)
{short_term_items_numbered}

### Medium-Term (This Quarter)
{medium_term_items_numbered}

### Backlog
{backlog_items_numbered}

Best Practices

When Analyzing Drift

  1. Compare timestamps, not just content

- When was the doc last updated vs. last code change? - Are milestones dated realistically?

  1. Look for patterns, not individual items

- One stale issue isn't drift; 10 stale issues is a pattern - One undocumented feature isn't drift; 5 undocumented features is

  1. Consider context

- Active development naturally has some drift - Mature projects should have minimal drift - Post-launch projects often have documentation lag

  1. Weight by impact

- User-facing drift matters more than internal - Public API drift matters more than implementation details

When Creating Plans

  1. Be actionable, not exhaustive

- Top 5 immediate items, not top 50 - Each item should be completable in reasonable time

  1. Group related items

- "Update authentication docs" not "Update login page docs" + "Update signup docs"

  1. Include success criteria

- How do we know this drift item is resolved?

  1. Balance categories

- All security first, but don't ignore everything else - Mix quick wins with important work

Data Collection (JavaScript)

The collectors.js module extracts data without LLM overhead:

GitHub Data

  • Open issues categorized by labels
  • Open PRs with draft status
  • Milestones with due dates
  • Stale items (> 90 days inactive)
  • Theme analysis from titles

Documentation Data

  • Parsed README, PLAN.md, CLAUDE.md, CHANGELOG.md
  • Checkbox completion counts
  • Section analysis
  • Feature lists

Code Data

  • Directory structure
  • Framework detection
  • Test framework presence
  • Health indicators (CI, linting, tests)

Semantic Analysis (Opus)

The plan-synthesizer receives all collected data and performs:

  1. Cross-referencing: Match documented features to implementation
  2. Drift identification: Find divergence patterns
  3. Gap analysis: Identify what's missing
  4. Prioritization: Context-aware ranking
  5. Report generation: Actionable recommendations

Example Input/Output

Collected Data (from collectors.js)

{
  "github": {
    "issues": [...],
    "categorized": { "bugs": [...], "features": [...] },
    "stale": [...]
  },
  "docs": {
    "files": { "README.md": {...}, "PLAN.md": {...} },
    "checkboxes": { "total": 15, "checked": 3 }
  },
  "code": {
    "frameworks": ["Express"],
    "health": { "hasTests": true, "hasCi": true }
  }
}

Analysis Output (from plan-synthesizer)

# Reality Check Report

## Executive Summary
Project has moderate drift: 8 stale priority issues and 20% plan completion.
Strong code health (tests + CI) but documentation lags implementation.

## Drift Analysis
### Priority Neglect
**Severity**: high
8 high-priority issues inactive for 60+ days...

## Prioritized Plan
### Immediate
1. Close #45 (already implemented)
2. Update README API section...

平台分布

Codex

34.79%
按下载量换算22

Claude

29.48%
按下载量换算19

Cursor

18.01%
按下载量换算11

Gemini CLI

9.54%
按下载量换算6

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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