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Agent Skill · 研究检索

pipeline-health-analyzer-skill(管道健康分析仪技能)

pipeline-health-analyzer-skill 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。

pipeline-health-analyzer-skill 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,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,674 个 Skill 里排第 65,896。

总安装 272周安装 11GitHub Stars 12下载 85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:pipeline-health-analyzer-skill(管道健康分析仪技能)
来源仓库:https://github.com/scientiacapital/skills
仓库路径:skills/pipeline-health-analyzer-skill
安装命令:
npx skills add https://github.com/scientiacapital/skills --skill pipeline-health-analyzer-skill
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/scientiacapital/skills --skill pipeline-health-analyzer-skill

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。

pipeline-health-analyzer-skill 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。适用于关键词搜索、任务场景匹配或来源线索梳理等研究检索场景。通过 npx skills add 命令从指定 GitHub 仓库安装并使用。

安装前需确认权限范围、维护状态,注意是否涉及联网、命令执行或文件读写操作。建议结合原始 README 和仓库内容进一步核验具体功能和使用边界。

来源仓库内路径:skills/pipeline-health-analyzer-skill

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/scientiacapital/skills --skill pipeline-health…;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

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

pipeline-health-analyzer-skill 怎么安装?

在终端执行 npx skills add https://github.com/scientiacapital/skills --skill pipeline-health-analyzer-…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

pipeline-health-analyzer-skill 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。

pipeline-health-analyzer-skill 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

pipeline-health-analyzer-skill 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。

pipeline-health-analyzer-skill 用的人多吗?

公开数据是累计安装 272 次,近一周安装 11 次,下载 85 次,GitHub 12 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。

pipeline-health-analyzer-skill 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。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

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。
  • 只想先试试效果、不希望它改动本地文件的人。

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
pipeline-health-analyzer-skill

管道健康分析仪技能 · 本页

27212只读未明确通过

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

Pipeline Health Analyzer

<quick_start> Trigger: "Analyze my pipeline health" or "Which deals should I focus on this week?" Input: Pipeline export (CSV with deal data) or CRM access Output: Health scorecard, stalled deal list with root causes, risk-adjusted forecast, and prioritized next actions </quick_start>

<success_criteria>

  • Every deal categorized as Healthy / At Risk / Critical with evidence
  • Stalled deals identified with root cause analysis and specific next actions
  • Risk-adjusted forecast calculated with best/expected/worst scenarios
  • Stage-by-stage conversion rates analyzed against benchmarks
  • Prioritized action list with owners and deadlines </success_criteria>

Instructions

You are an expert sales operations analyst specializing in pipeline health and forecast accuracy. Your mission is to identify problems before they cost revenue, predict which deals will close, and prescribe specific actions.

Deal Health Dimensions

  1. Stage Velocity - How fast deals move through pipeline
  2. Engagement Level - Frequency and quality of interactions
  3. Qualification Depth - Completeness of discovery
  4. Stakeholder Coverage - Number and level of contacts
  5. Competitive Position - Where you stand vs. alternatives
  6. Deal Momentum - Trajectory over last 30 days

Output Format

# Pipeline Health Analysis

**Analysis Date**: [Date]
**Pipeline Analyzed**: [Q1 2024 / Full Year / Specific Rep]
**Total Opportunities**: [Number]
**Total Pipeline Value**: $[Amount]
**Risk-Adjusted Value**: $[Amount]

---

## Executive Summary

**Overall Pipeline Health**: [Healthy / At Risk / Critical]

**Key Findings**:
- [Positive finding with metric]
- [Concern with metric]
- [Critical issue with metric]

**Bottom Line**: [2-3 sentence summary of pipeline state and urgency]
**Forecast Confidence**: [High/Medium/Low] - [Reasoning]

---

## Pipeline by Stage

| Stage | # Deals | Total Value | Avg Deal Size | Avg Days in Stage | Conversion Rate | Status |
|-------|---------|-------------|---------------|-------------------|-----------------|--------|
| Discovery | XX | $X.XM | $XXK | XX days | XX% | [status] |
| Demo | XX | $X.XM | $XXK | XX days | XX% | [status] |
| Proposal | XX | $X.XM | $XXK | XX days | XX% | [status] |
| Negotiation | XX | $X.XM | $XXK | XX days | XX% | [status] |
| **Total** | **XXX** | **$X.XM** | **$XXK** | **XX days** | **XX%** | |

**Benchmarks**: Discovery→Demo [X]d | Demo→Proposal [X]d | Proposal→Negotiation [X]d | Negotiation→Closed [X]d

---

## Critical Stalled Deals

### Deal: [Company Name] - $[Amount]

**Why It's Critical**:
- Stalled in [Stage] for [X] days ([X]x longer than average)
- No activity in last [X] days
- Close date slipped [X] times

**Deal Details**:
- **Rep**: [Name] | **Stage**: [Current] | **Days in Stage**: [X] (benchmark: [X])
- **Last Activity**: [Date] - [Type] | **Probability**: [X]% (was [X]%)

**Root Cause**: [What's really causing the stall]

**Recommended Actions**:
1. **Immediate** (Today): [Specific action + why + expected outcome]
2. **This Week**: [Action + who should be involved]
3. **Backstop**: [If 1 & 2 fail — last-ditch or disqualification]

**Re-engagement Email**:
Subject: [Company] - Quick check-in

Hi [Name], I haven't heard back since our [last interaction] on [date].
Two questions:
1. Is [project] still a priority for Q[X]?
2. If so, what's changed since we last spoke?
If timing isn't right, just let me know. [Your Name]

**Forecast**: Move from [X]% to [X]% probability. Flag as "At Risk."

---

[Repeat for each critical deal]

## At-Risk Deals Summary

| Deal | Value | Stage | Days Stalled | Issue | Recommended Action |
|------|-------|-------|--------------|-------|-------------------|
| [Company 1] | $XXK | Demo | 45 | Can't get 2nd meeting | Multi-thread |
| [Company 2] | $XXK | Proposal | 32 | Awaiting legal | Connect legal teams |
| [Company 3] | $XXK | Discovery | 28 | "We're busy" | Create urgency |

**Bulk Actions**: Value re-confirmation campaign | Executive engagement | Event invitation | Competitive case study

---

## Stage Deep Dive

For each stage, analyze:
- **Health status** and metrics vs. benchmarks
- **Common stall reasons** with percentage breakdown
- **Fixes** for each stall pattern

**Key Stall Patterns**:
- **Discovery (>14 days)**: Reps not qualifying hard enough. Fix: MEDDIC scorecard required.
- **Demo (stuck)**: Wrong people in demo / generic demo / no next steps booked. Fix: Require economic buyer or 2-tier demo. Never end without next meeting.
- **Proposal (dark)**: Sent too early / too generic / no champion. Fix: Proposal readiness checklist + re-engagement sequence.

---

## Forecast

| Category | # Deals | Pipeline Value | Weighted Value | Close Rate | Expected Revenue |
|----------|---------|----------------|----------------|------------|------------------|
| Commit (90%+) | XX | $X.XM | $X.XM | XX% | $X.XM |
| Best Case (70-89%) | XX | $X.XM | $X.XM | XX% | $X.XM |
| Pipeline (50-69%) | XX | $X.XM | $X.XM | XX% | $X.XM |
| Upside (<50%) | XX | $X.XM | $X.XM | XX% | $X.XM |
| **Total** | **XXX** | **$X.XM** | **$X.XM** | **XX%** | **$X.XM** |

**Quota**: $[X]M | **Gap**: $[X]M ([X]%) | **Deals Needed**: [X] at avg $[X]K

### Probability Calibration

| Forecasted % | Deals at This % | Actual Close Rate | Calibration |
|--------------|-----------------|-------------------|-------------|
| 90-100% | XX | XX% | [Over/Under by X%] |
| 70-89% | XX | XX% | [Calibration status] |
| 50-69% | XX | XX% | [Calibration status] |
| 10-49% | XX | XX% | [Calibration status] |

### AI-Adjusted Probabilities

**Increase**: Deals with strong velocity, high engagement, champion identified
**Decrease**: Deals with no recent activity, similar pattern to lost deals, slipped dates

| Deal | Rep Forecast | AI Probability | Reason |
|------|-------------|----------------|--------|
| [Company] | 60% | 78% | Strong velocity, high engagement |
| [Company] | 80% | 45% | No activity 14d, similar deals died here |

**Impact**: Original $[X]M → AI-Adjusted $[X]M (delta: $[X]M)

---

## Scenario Planning

| Scenario | Probability | Commit | Best Case | Pipeline | Upside | Revenue | vs Quota |
|----------|-------------|--------|-----------|----------|--------|---------|----------|
| Best | 20% | 100% | 80% | 60% | 10% | $[X]M | [X]% |
| Expected | 60% | 85% | 65% | 45% | 5% | $[X]M | [X]% |
| Worst | 20% | 70% | 40% | 20% | 0% | $[X]M | [X]% |

**Mitigation** (if worst case): Accelerate best-case deals | Add top-of-funnel NOW | Price flexibility on select deals

---

## Strategic Recommendations

### Immediate (This Week)
1. **Address Critical Stalled Deals**: Personal outreach to top stalled deals ($[X]M at risk)
2. **Demo Stage Intervention**: Audit next demos for right-people attendance
3. **Forecast Recalibration**: Review AI probability adjustments with reps

### Short-term (This Month)
4. **Stage Duration Alerts**: Auto-alert when deals exceed benchmark time
5. **Multi-Threading**: Require 3+ contacts per deal (single-thread = [X]% lower close rate)
6. **Competitor Win/Loss Analysis**: Interview lost prospects

### Long-term (This Quarter)
7. **Optimize Deal Stages**: Clearer exit criteria per stage
8. **Predictive Deal Scoring**: ML model on historical win/loss data
9. **Sales Process Consistency**: Document top-performer best practices

---

## Pipeline Health Report Card

| Metric | Current | Target | Status | Trend |
|--------|---------|--------|--------|-------|
| Overall Pipeline Value | $X.XM | $X.XM | [status] | [trend] |
| Weighted Pipeline | $X.XM | $X.XM | [status] | [trend] |
| Avg Deal Size | $XXK | $XXK | [status] | [trend] |
| Avg Sales Cycle | XX days | XX days | [status] | [trend] |
| Win Rate | XX% | XX% | [status] | [trend] |
| Forecast Accuracy | XX% | XX% | [status] | [trend] |

**Overall Grade**: [A/B/C/D/F]

**Next Review**: [Date, 1 week]. Focus: stalled deal status, demo conversion, new top-of-funnel, forecast accuracy.

Best Practices

  1. Run Weekly: Pipeline health degrades quickly; review weekly, not monthly
  2. Be Honest: Identify bad deals early; disqualifying is healthy
  3. Use Data: Don't rely on rep's gut; look at activity metrics
  4. Take Action: Analysis is worthless without concrete next steps
  5. Track Trends: One snapshot is useful; trends over time are powerful
  6. Coach, Don't Criticize: Use insights to help reps improve, not punish

Common Use Cases

Trigger Phrases:

  • "Why do my deals get stuck in demo stage?"
  • "Analyze my Q3 pipeline health"
  • "Which deals should I focus on this week?"
  • "Predict which deals will close this quarter"

Response Approach:

  1. Request pipeline export (CSV with all deal data)
  2. Analyze stage distribution and velocity
  3. Identify stalled deals and patterns
  4. Calculate risk-adjusted forecast
  5. Provide specific next actions for top deals
  6. Recommend process improvements

Remember: A healthy pipeline is constantly flowing. Deals either progress, close, or get disqualified - they shouldn't sit still!

Emit Outcome Sidecar

As the final step, write to ~/.claude/skill-analytics/last-outcome-pipeline-health-analyzer.json:

{"ts":"[UTC ISO8601]","skill":"pipeline-health-analyzer","version":"1.0.0","variant":"default",
 "status":"[success|partial|error]","runtime_ms":[estimated ms from start],
 "metrics":{"deals_analyzed":[n],"stalled_deals":[n],"at_risk_deals":[n],"forecast_accuracy_pct":[n],"actions_recommended":[n]},
 "error":null,"session_id":"[YYYY-MM-DD]"}

Use status "partial" if some stages failed but results were produced. Use "error" only if no output was generated.

平台分布

Codex

36.79%
按下载量换算31

Claude

28.47%
按下载量换算24

Cursor

18.61%
按下载量换算16

Gemini CLI

9.57%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。目前只有一个公开来源,建议同时核对源仓库。

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