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Agent Skill · 开发

analytics-flow(分析流程)

用于辅助数据整理、表格处理、CSV/Excel 分析、指标计算和图表准备。它适合让 Agent 清洗字段、汇总数据、发现异常、生成统计口径或把分析结果转成可读说明。使用时需要确认数据来源、字段含义和时间范围,避免把样本数据当全量事实;涉及敏感数据、导出文件或批量写回时,应先确认权限和脱敏边界。

analytics-flow 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证为 MIT,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 12,384。

总安装 1,310周安装 53GitHub Stars 14下载 411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
MIT

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:analytics-flow(分析流程)
来源仓库:https://github.com/vladm3105/aidoc-flow-framework
仓库路径:skills/analytics-flow
安装命令:
npx skills add https://github.com/vladm3105/aidoc-flow-framework --skill analytics-flow
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/vladm3105/aidoc-flow-framework --skill analytics-flow

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

追踪项目文档覆盖率、进度与质量指标,生成可视化分析报告。识别文档过期风险与需求覆盖缺口,辅助团队优化工作流程。集成 SDD 工件分析,提供开发速度与瓶颈洞察。需配置文档目录与类型映射规则,确保数据整理口径一致。analytics-flow 属于开发类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/analytics-flow

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/vladm3105/aidoc-flow-framework --skill analyti…;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

    它需要调用外部服务,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

analytics-flow 怎么安装?

在终端执行 npx skills add https://github.com/vladm3105/aidoc-flow-framework --skill analytics-flow。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

analytics-flow 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。

analytics-flow 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

analytics-flow 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

analytics-flow 用的人多吗?

公开数据是累计安装 1,310 次,近一周安装 53 次,下载 411 次,GitHub 14 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。

analytics-flow 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 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。
  • 需要处理开发类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
analytics-flow

分析流程 · 本页

1,31014调用外部服务MIT通过

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

analytics-flow

Description: Project metrics, documentation analytics, progress tracking, and trend analysis

Category: Data Analysis & Reporting

Complexity: Medium (data aggregation + visualization)


Purpose

Provide visibility into project progress, documentation quality, requirement coverage, and development velocity. Generate actionable insights from SDD artifacts to identify bottlenecks and optimize workflows.


Capabilities

1. Documentation Coverage Metrics

  • Total documents by type (BRD, PRD, REQ, BDD, etc.)
  • Token count distribution
  • Documentation completeness percentage
  • Outdated document identification
  • Documentation debt tracking

2. Requirement Tracking

  • Total requirements by category
  • Requirement status (draft, approved, implemented, tested)
  • Requirement coverage (REQ → BDD → TASK mapping)
  • Orphaned requirements
  • Requirement age and staleness

3. Traceability Analysis

  • Complete traceability chains (BRD →... → Code)
  • Broken traceability links
  • Traceability coverage percentage
  • Gap identification
  • Circular dependency detection

4. Implementation Progress

  • Tasks completed vs total
  • Implementation phase progress
  • Blocked vs active tasks
  • Timeline adherence
  • Milestone tracking

5. Velocity Tracking

  • Requirements completed per sprint/week
  • Implementation velocity
  • Documentation velocity
  • Test coverage velocity
  • Trend analysis over time

6. Quality Metrics

  • Code review scores over time
  • Test coverage trends
  • Security vulnerability trends
  • Code complexity trends
  • Documentation quality scores

7. Bottleneck Identification

  • Stuck requirements (no progress)
  • Blocked tasks
  • Resource constraints
  • Dependency chains blocking progress
  • Review bottlenecks

8. Custom Report Generation

  • Executive summaries
  • Sprint/weekly reports
  • Milestone reports
  • Team performance reports
  • Risk assessment reports

Analytics Workflow

graph TD
    A[SDD Artifacts] --> B[Data Collection]
    B --> C[Parse Documents]
    C --> D[Extract Metadata]

    D --> E[Requirement Analysis]
    D --> F[Traceability Analysis]
    D --> G[Progress Analysis]
    D --> H[Quality Analysis]

    E --> I[Requirement Metrics]
    F --> J[Traceability Matrix]
    G --> K[Progress Dashboard]
    H --> L[Quality Dashboard]

    I --> M[Aggregate Data]
    J --> M
    K --> M
    L --> M

    M --> N[Calculate KPIs]
    N --> O[Identify Trends]
    O --> P[Detect Anomalies]
    P --> Q[Generate Insights]

    Q --> R{Report Type}
    R -->|Executive| S[Executive Summary]
    R -->|Technical| T[Technical Report]
    R -->|Sprint| U[Sprint Report]

    S --> V[Distribute Reports]
    T --> V
    U --> V

Usage Instructions

Generate Project Dashboard

analytics-flow dashboard --output reports/dashboard.html

Generated dashboard sections:

Project Overview Dashboard
==========================

Overall Health: 78/100 (Good)

Documentation Coverage:
├─ BRD Documents: 3/3 (100%) ✓
├─ PRD Documents: 2/3 (67%) ⚠️
├─ Requirements: 146/150 (97%) ✓
├─ BDD Scenarios: 89/146 (61%) ⚠️
├─ ADR Documents: 12/12 (100%) ✓
├─ SPEC Documents: 5/8 (63%) ⚠️
└─ TASK Documents: 45/89 (51%) ❌

Implementation Progress:
├─ Phase 1: 100% (Completed) ✓
├─ Phase 2: 75% (In Progress) →
├─ Phase 3: 0% (Not Started) ○
└─ Overall: 58% complete

Traceability Coverage:
├─ Forward Traceability: 94% ✓
├─ Backward Traceability: 91% ✓
└─ Complete Chains: 87% ✓

Quality Metrics:
├─ Code Coverage: 87% ✓
├─ Code Review Score: 82/100 ✓
├─ Security Issues: 3 (1 Critical) ⚠️
└─ Documentation Quality: 89% ✓

Velocity (Last 4 Weeks):
├─ Requirements: 12/week (avg)
├─ Implementation: 8 tasks/week
├─ Tests Written: 45 tests/week
└─ Trend: ↗ Improving

Bottlenecks Identified:
├─ REQ-AUTH-015: Stuck for 3 weeks
├─ BDD Scenarios: 39% gap vs requirements
└─ Phase 2 Dependency: Blocked by external API

Generate Requirement Report

analytics-flow requirements --format json --output reports/requirements.json

Output:

{
  "summary": {
    "total_requirements": 146,
    "by_priority": {
      "MUST": 130,
      "SHOULD": 12,
      "MAY": 4
    },
    "by_status": {
      "draft": 5,
      "approved": 85,
      "implemented": 45,
      "tested": 38,
      "deployed": 30
    },
    "by_category": {
      "authentication": 15,
      "authorization": 12,
      "data_processing": 45,
      "api": 38,
      "ml_models": 32,
      "infrastructure": 4
    }
  },
  "coverage": {
    "with_bdd_scenarios": 89,
    "with_tasks": 78,
    "with_tests": 67,
    "complete_traceability": 127
  },
  "age_analysis": {
    "average_age_days": 45,
    "oldest_requirement": {
      "id": "REQ-AUTH-01",
      "age_days": 120,
      "status": "implemented"
    },
    "stale_requirements": [
      {"id": "REQ-ML-015", "age_days": 90, "status": "draft"}
    ]
  },
  "orphaned_requirements": [
    "REQ-AUTH-015",
    "REQ-DATA-023"
  ]
}

Generate Traceability Matrix

analytics-flow traceability --format mermaid --output reports/traceability.mmd

Generated Mermaid diagram:

graph LR
    BRD001[BRD-SYSTEM-001] --> PRD001[PRD-FEATURES-001]
    PRD001 --> REQ001[REQ-AUTH-01]
    PRD001 --> REQ002[REQ-AUTH-002]

    REQ001 --> BDD001[BDD-LOGIN-001]
    REQ001 --> BDD002[BDD-LOGIN-002]
    REQ002 --> BDD003[BDD-LOGOUT-001]

    BDD001 --> TASK001[TASK-AUTH-001]
    BDD002 --> TASK002[TASK-AUTH-002]
    BDD003 --> TASK003[TASK-AUTH-003]

    TASK001 --> CODE001[auth/login.py]
    TASK002 --> CODE001
    TASK003 --> CODE002[auth/logout.py]

    CODE001 --> TEST001[test_login.py]
    CODE002 --> TEST002[test_logout.py]

    style BRD001 fill:#e1f5ff
    style PRD001 fill:#e8f5e9
    style REQ001 fill:#fff3e0
    style REQ002 fill:#fff3e0
    style BDD001 fill:#f3e5f5
    style BDD002 fill:#f3e5f5
    style BDD003 fill:#f3e5f5

Generate Sprint Report

analytics-flow sprint \
  --start-date 2025-01-01 \
  --end-date 2025-01-14 \
  --output reports/sprint-report.md

Generated report:

# Sprint Report: Jan 1-14, 2025

## Sprint Summary
- Duration: 2 weeks
- Team Size: 5 developers
- Sprint Goal: Complete Phase 2 authentication features

## Accomplishments
✓ Completed: 12 requirements
✓ Implemented: 18 tasks
✓ Tests Written: 67 tests
✓ Code Coverage: 87% → 91% (+4%)

## Requirements Completed
1. REQ-AUTH-01: User login with JWT ✓
2. REQ-AUTH-002: User logout ✓
3. REQ-AUTH-003: Password reset ✓
4. REQ-AUTH-004: Email verification ✓
... (8 more)

## Velocity Metrics
- Requirements: 6/week (target: 5/week) ↗
- Tasks: 9/week (target: 8/week) ↗
- Tests: 33.5/week (target: 25/week) ↗

## Quality Metrics
- Code Review Score: 85/100 (+3 from last sprint)
- Security Issues: 2 (down from 5)
- Test Coverage: 91% (up from 87%)

## Blockers Resolved
1. External API integration (blocked 5 days) → Resolved
2. Database migration issue → Resolved

## Current Blockers
1. Waiting for design review on user profile page (2 days)

## Risks
⚠️ Phase 3 dependency on external service (mitigation: mock implementation)

## Next Sprint Goals
- Complete remaining 8 authentication requirements
- Begin authorization framework
- Improve test coverage to 93%

Track Velocity Trends

analytics-flow velocity --weeks 12 --output reports/velocity.json

Output with trend analysis:

{
  "period": "12 weeks",
  "metrics": [
    {
      "week": "2025-W01",
      "requirements_completed": 8,
      "tasks_completed": 15,
      "tests_written": 42,
      "code_coverage": 85
    },
    {
      "week": "2025-W02",
      "requirements_completed": 12,
      "tasks_completed": 18,
      "tests_written": 67,
      "code_coverage": 91
    }
  ],
  "trends": {
    "requirements": {
      "average": 10,
      "trend": "increasing",
      "velocity_change": "+15%"
    },
    "tasks": {
      "average": 16.5,
      "trend": "stable",
      "velocity_change": "+2%"
    },
    "tests": {
      "average": 54.5,
      "trend": "increasing",
      "velocity_change": "+25%"
    }
  },
  "forecast": {
    "next_sprint_requirements": 13,
    "completion_date_phase_2": "2025-02-15",
    "confidence": "high"
  }
}

Key Performance Indicators (KPIs)

Documentation KPIs

  1. Documentation Coverage Coverage = (Completed Documents / Total Required Documents) × 100% Target: ≥95%
  2. Documentation Debt Debt = Outdated Documents + Missing Documents Target: <5% of total documents
  3. Average Document Age Age = Days since last update Target: <30 days for active documents

Requirement KPIs

  1. Requirement Coverage Coverage = (Requirements with Tests / Total Requirements) × 100% Target: 100% for MUST requirements
  2. Requirement Cycle Time Cycle Time = Days from draft to deployed Target: <14 days (2 sprints)
  3. Orphaned Requirements Orphaned = Requirements without forward/backward links Target: 0

Implementation KPIs

  1. Implementation Velocity Velocity = Tasks completed / Time period Track: Weekly, calculate 4-week moving average
  2. Task Completion Rate Completion = (Completed Tasks / Total Tasks) × 100% Target: ≥90% per sprint
  3. Blocked Task Percentage Blocked % = (Blocked Tasks / Active Tasks) × 100% Target: <10%

Traceability KPIs

  1. Forward Traceability Forward = (Requirements with downstream links / Total Requirements) × 100% Target: 100%
  2. Backward Traceability Backward = (Tasks with upstream links / Total Tasks) × 100% Target: 100%
  3. Complete Traceability Chains Complete = (Requirements with full BRD→Code chain / Total) × 100% Target: ≥95%

Quality KPIs

  1. Code Coverage Trend Track: Weekly, target: ≥90% Alert: If drops >5% week-over-week
  2. Code Review Score Track: Per PR, target: ≥80/100 Alert: If average <70 for 2 consecutive weeks
  3. Security Vulnerability Density Density = Critical vulnerabilities / KLOC Target: 0 critical vulnerabilities

Report Templates

Executive Summary Template

# Executive Project Summary
Date: {date}
Period: {period}

## Overall Status: {status_indicator}

### Progress
- Phase Completion: {phase_progress}%
- On Schedule: {schedule_status}
- Budget Status: {budget_status}

### Key Achievements
1. {achievement_1}
2. {achievement_2}
3. {achievement_3}

### Risks & Mitigation
| Risk | Impact | Probability | Mitigation |
|------|--------|-------------|------------|
| {risk_1} | {impact} | {prob} | {mitigation} |

### Next Milestone
- {milestone_name}: {milestone_date}
- {deliverables}

### Resource Requirements
- {resource_needs}

Technical Report Template

# Technical Project Report
Date: {date}

## Architecture
- ADRs Approved: {adr_count}
- Major Decisions: {decisions_summary}

## Implementation
- Requirements Completed: {req_completed}/{req_total}
- Code Coverage: {coverage}%
- Technical Debt: {tech_debt_score}

## Quality Metrics
- Code Review Score: {review_score}/100
- Security Issues: {security_count}
- Performance Benchmarks: {performance_data}

## Infrastructure
- Environments: {env_status}
- Deployments: {deployment_count}
- Uptime: {uptime}%

## Traceability
- Forward Coverage: {forward_trace}%
- Backward Coverage: {backward_trace}%
- Gaps: {gap_count}

Data Sources

Primary Sources

  • All SDD artifact files (BRD, PRD, REQ, BDD, ADR, SPEC, TASK, CTR)
  • Git commit history
  • Test execution results
  • Code coverage reports
  • Security scan results
  • CI/CD pipeline logs

Derived Metrics

  • Velocity calculations
  • Trend analysis
  • Predictive forecasting
  • Anomaly detection

Visualization Options

Chart Types

  1. Burndown Chart: Sprint/project progress
  2. Velocity Chart: Weekly implementation velocity
  3. Coverage Trend: Test coverage over time
  4. Traceability Matrix: Requirement-to-code mapping
  5. Dependency Graph: Task dependencies
  6. Risk Heat Map: Risk probability vs impact
  7. Quality Dashboard: Multi-metric visualization

Export Formats

  • HTML dashboards (interactive)
  • PDF reports (static)
  • JSON data (for integration)
  • Markdown reports (for Git)
  • Mermaid diagrams (for documentation)
  • CSV data (for spreadsheets)

Tool Access

Required tools:

  • Read: Read all SDD artifacts
  • Glob: Find all documents
  • Grep: Search for patterns and IDs
  • Bash: Execute analysis scripts

Required libraries:

  • pandas: Data analysis
  • matplotlib/plotly: Visualization
  • jinja2: Report templating
  • pyyaml: YAML parsing

Integration Points

With doc-flow

  • Extract metadata from generated documents
  • Track documentation workflow progress
  • Identify documentation gaps

With test-automation

  • Aggregate test coverage data
  • Track test execution trends
  • Correlate tests with requirements

With code-review

  • Track code quality trends
  • Aggregate review scores
  • Identify quality patterns

With project-mngt

  • Validate timeline adherence
  • Track milestone progress
  • Resource utilization analysis

Best Practices

  1. Update frequency: Daily automated collection, weekly reports
  2. Baseline establishment: Set baseline metrics at project start
  3. Trend analysis: Focus on trends, not absolute numbers
  4. Actionable insights: Every metric should inform decisions
  5. Anomaly detection: Alert on unusual patterns
  6. Historical data: Maintain 6+ months of history
  7. Stakeholder alignment: Customize reports per audience
  8. Continuous improvement: Evolve metrics based on feedback

Limitations

  1. Requires consistent SDD artifact structure
  2. Historical analysis limited to available data
  3. Predictive accuracy depends on data quality
  4. Cannot measure subjective quality factors
  5. Requires regular data collection for accuracy

Success Criteria

  • Real-time dashboard availability
  • <5 minute report generation time
  • 100% data accuracy
  • All KPIs tracked automatically
  • Trend analysis with 90% forecast accuracy
  • Zero manual data collection required
  • Stakeholder satisfaction ≥4/5

Notes

  • Reports saved to reports/analytics/
  • Historical data stored in metrics/history.json
  • Dashboard auto-refreshes every 15 minutes
  • Alerts configured for KPI threshold breaches
  • Custom metrics configurable via .analytics.yml

平台分布

Gemini CLI

27.14%
按下载量换算112

Claude Code

21.59%
按下载量换算89

Antigravity

17.51%
按下载量换算72

OpenCode

13.52%
按下载量换算56

Codex

8.59%
按下载量换算35

windsurf

3.49%
按下载量换算14

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。

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