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Agent Skill · 研究检索

estimation(estimation 搜索)

estimation 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。

estimation 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;许可证为 MIT,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 42,343。

总安装 1,082周安装 46GitHub Stars 61下载 379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:estimation(estimation 搜索)
来源仓库:https://github.com/melodic-software/claude-code-plugins
仓库路径:skills/estimation
安装命令:
npx skills add https://github.com/melodic-software/claude-code-plugins --skill estimation
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/melodic-software/claude-code-plugins --skill estimation

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。

estimation 运用类比法、参数法与专家判断等多种成熟估算技术。支持项目周期、人力投入、成本预算与难度等级多维评估。遵循行业最佳实践,确保估算结果具备可重复性与可比性。适用于新项目启动前的可行性分析与资源预申请场景。estimation 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/estimation

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/melodic-software/claude-code-plugins --skill e…;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

estimation 怎么安装?

在终端执行 npx skills add https://github.com/melodic-software/claude-code-plugins --skill estimation。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

estimation 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。

estimation 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。

estimation 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。

estimation 用的人多吗?

公开数据是累计安装 1,082 次,近一周安装 46 次,下载 379 次,GitHub 61 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。

estimation 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。
  • 需要处理研究检索类任务、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。

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
estimation

estimation 搜索 · 本页

1,08261需要联网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

Estimation

When to Use This Skill

Use this skill when:

  • Estimation tasks - Working on estimation techniques including analogous, parametric, three-point, and expert judgment methods. provides effort, cost, duration, and complexity estimates for projects, features, and tasks
  • Planning or design - Need guidance on Estimation approaches
  • Best practices - Want to follow established patterns and standards

Overview

Systematically estimate effort, cost, duration, and complexity using proven estimation techniques. Supports analogous, parametric, three-point (PERT), and expert judgment methods for projects, features, and tasks.

What is Estimation?

Estimation is the process of forecasting the resources, time, and cost required to complete work. Good estimation balances:

  • Accuracy: How close to actual results
  • Precision: Consistency of estimates
  • Speed: Time to produce estimates
  • Communication: Shared understanding of uncertainty

Estimation vs Commitment

ConceptDefinitionUse
EstimateBest guess given current knowledgePlanning, forecasting
CommitmentPromise to deliver by date/costContracts, deadlines
TargetDesired outcome to aim forGoals, objectives

Key principle: Estimates are ranges with uncertainty, not single-point guarantees.

Estimation Techniques

Analogous Estimation (Top-Down)

Estimate based on similar past work:

StepAction
1Identify similar completed project/feature
2Retrieve actual effort/cost/duration
3Adjust for differences (complexity, team, technology)
4Apply adjustment factor

Formula:

New Estimate = Historical Actual × Adjustment Factor

Example:
Similar project took 200 hours
New project is ~20% more complex
Estimate = 200 × 1.20 = 240 hours

When to Use: Early phases, limited detail, experienced teams with historical data

Accuracy: +/- 25-50% (improves with good historical data)

Parametric Estimation

Estimate using statistical relationships:

ElementDescription
Unit of WorkMeasurable element (screen, API, table)
Productivity RateEffort per unit from historical data
QuantityNumber of units to produce

Formula:

Estimate = Quantity × Productivity Rate

Example:
10 API endpoints × 16 hours/endpoint = 160 hours

Common Productivity Metrics:

Work TypeMetricTypical Range
UI screensHours/screen8-40 hours
API endpointsHours/endpoint4-24 hours
Database tablesHours/table4-16 hours
Test casesHours/test0.5-4 hours
Documentation pagesHours/page2-8 hours

When to Use: Repeatable work, good historical data, similar technology

Accuracy: +/- 15-25% (with calibrated rates)

Three-Point Estimation (PERT)

Estimate using optimistic, most likely, and pessimistic values:

ValueSymbolDefinition
OptimisticOBest case, everything goes right
Most LikelyMMost probable outcome
PessimisticPWorst case, problems occur

PERT Formula (Weighted Average):

Expected = (O + 4M + P) / 6
Standard Deviation = (P - O) / 6

Example:
O = 5 days, M = 8 days, P = 17 days
Expected = (5 + 4×8 + 17) / 6 = 9 days
Std Dev = (17 - 5) / 6 = 2 days

Confidence Intervals:

ConfidenceCalculationExample (E=9, SD=2)
68%E ± 1 SD7-11 days
95%E ± 2 SD5-13 days
99.7%E ± 3 SD3-15 days

When to Use: Uncertain work, new technology, need to communicate risk

Accuracy: Provides explicit uncertainty range

Expert Judgment

Estimate using collective expert knowledge:

Wideband Delphi Process:

RoundActivity
1Experts estimate independently
2Collect and share anonymous estimates
3Discuss high/low outliers, share rationale
4Re-estimate independently
5Repeat until convergence (or average)

Planning Poker (Agile):

StepAction
1Present item to estimate
2Discuss briefly (2-5 minutes)
3Each team member selects card privately
4Reveal simultaneously
5Discuss outliers
6Re-vote until consensus

Common Scales:

Scale TypeValues
Fibonacci1, 2, 3, 5, 8, 13, 21, 34, 55, 89
Modified Fibonacci0, 0.5, 1, 2, 3, 5, 8, 13, 20, 40, 100
T-shirtXS, S, M, L, XL, XXL
Powers of 21, 2, 4, 8, 16, 32, 64

When to Use: Complex work, multiple perspectives needed, team alignment

Function Point Analysis

Estimate based on functional size (for larger systems):

ComponentDescriptionWeight Range
External InputsData entering system3-6
External OutputsData leaving system4-7
External InquiriesRead-only queries3-6
Internal FilesLogical data stores7-15
External InterfacesShared data5-10

Process:

  1. Count each component type
  2. Classify complexity (low/medium/high)
  3. Apply weights
  4. Calculate unadjusted function points
  5. Apply technical complexity factor

When to Use: Large projects, formal contracts, industry benchmarking

Relative Estimation

Story Points

Relative complexity/effort measure:

PointsRelative SizeExample
1TrivialFix typo, config change
2SimpleSimple bug fix, minor feature
3ModerateStandard feature, moderate complexity
5ComplexMulti-component feature
8Very complexIntegration work, significant unknowns
13Epic-sizedConsider breaking down
21+Too largeMust decompose

Baseline: Pick a well-understood story as reference (e.g., "this is a 3")

Velocity: Story points completed per iteration (used for forecasting)

T-Shirt Sizing

Quick relative sizing for roadmap planning:

SizeEffort RangeDuration Range
XS1-4 hours< 1 day
S0.5-2 days1-2 days
M2-5 days3-5 days
L1-2 weeks1-2 weeks
XL2-4 weeks2-4 weeks
XXL1-3 monthsToo big, decompose

Workflow

Phase 1: Prepare

Step 1: Clarify Scope
## Estimation Request

**Item:** [What's being estimated]
**Requester:** [Who needs the estimate]
**Purpose:** [Planning/budgeting/commitment]
**Deadline:** [When estimate is needed]
**Precision:** [ROM/Budget/Definitive]

### Scope Definition

- **In Scope:** [What's included]
- **Out of Scope:** [What's excluded]
- **Assumptions:** [Key assumptions]
- **Constraints:** [Known constraints]
Step 2: Select Estimation Technique
SituationRecommended Technique
Early project phaseAnalogous + T-shirt sizing
Detailed requirementsParametric + Three-point
Agile backlogStory points + Planning poker
New technology/domainExpert judgment + Three-point
Contract/budgetFunction points + Parametric

Phase 2: Estimate

Step 1: Decompose Work

Break down into estimable units (half-day to 2-week chunks)

Step 2: Apply Technique

Use selected technique(s) from above

Step 3: Add Contingency
## Contingency Calculation

| Risk Level | Contingency | When to Use |
|------------|-------------|-------------|
| Low | 10-15% | Well-understood, experienced team |
| Medium | 20-30% | Some unknowns, new team members |
| High | 40-50% | Significant unknowns, new technology |
| Very High | 75-100% | Research, innovation, first-of-kind |
Step 4: Validate
  • Sanity check against similar work
  • Review with team
  • Check for missing items
  • Verify assumptions

Phase 3: Communicate

Step 1: Express as Range
## Estimate Summary

**Effort:** 160-200 hours (confidence: 80%)
**Duration:** 4-5 weeks (with 2 developers)
**Cost:** $24,000-$30,000

**Key Risks:**
- API integration complexity unknown
- Dependency on third-party availability
Step 2: Document Assumptions
## Estimation Assumptions

1. Requirements are stable and complete
2. Team has 80% availability (20% overhead)
3. No major technology changes
4. Dependencies delivered on time
5. [Additional assumptions...]

**If assumptions change, estimate should be revisited.**

Output Formats

Narrative Summary

## Estimation Summary

**Item:** [Feature/Project name]
**Date:** [ISO date]
**Estimator:** estimation-analyst
**Technique:** [Technique used]

### Estimate

| Dimension | Low | Expected | High | Confidence |
|-----------|-----|----------|------|------------|
| Effort | 120h | 160h | 220h | 80% |
| Duration | 4w | 5w | 7w | 80% |
| Cost | $18K | $24K | $33K | 80% |

### Basis of Estimate

- **Historical Reference:** [Similar past work]
- **Productivity Rate:** [If parametric]
- **Expert Input:** [Who contributed]

### Assumptions

1. [Assumption 1]
2. [Assumption 2]

### Risks Affecting Estimate

| Risk | Impact on Estimate |
|------|-------------------|
| [Risk 1] | +20% if occurs |
| [Risk 2] | +15% if occurs |

### Recommendations

1. [Next steps for refining estimate]
2. [When to re-estimate]

Structured Data (YAML)

estimation:
  version: "1.0"
  date: "2025-01-15"
  item: "User Dashboard Feature"
  estimator: "estimation-analyst"
  technique: "three_point"

  scope:
    description: "Interactive user dashboard with analytics"
    in_scope:
      - "Dashboard UI components"
      - "Data visualization"
      - "User preferences"
    out_of_scope:
      - "Backend analytics engine"
      - "Real-time updates"
    assumptions:
      - "API endpoints available"
      - "Design mockups complete"

  estimates:
    effort:
      optimistic: 120
      most_likely: 160
      pessimistic: 240
      expected: 166
      unit: "hours"
      std_deviation: 20
    duration:
      optimistic: 3
      most_likely: 4
      pessimistic: 6
      expected: 4.2
      unit: "weeks"
    cost:
      expected: 24000
      range_low: 18000
      range_high: 36000
      currency: "USD"

  confidence: 0.80
  contingency: 0.20

  breakdown:
    - component: "UI Components"
      effort: 60
      technique: "parametric"
      rate: "15h/component"
      quantity: 4
    - component: "Data Integration"
      effort: 40
      technique: "analogous"
      reference: "PROJ-123"
    - component: "Testing"
      effort: 40
      technique: "percentage"
      percentage: 0.25

  risks:
    - risk: "API complexity higher than expected"
      probability: 0.3
      impact_hours: 30
    - risk: "Design changes during development"
      probability: 0.2
      impact_hours: 20

  historical_comparison:
    similar_item: "Admin Dashboard"
    actual_effort: 180
    adjustment_factor: 0.9

Breakdown Table

## Effort Breakdown

| Component | Technique | Estimate | Contingency | Total |
|-----------|-----------|----------|-------------|-------|
| UI Components | Parametric | 60h | 12h | 72h |
| Data Integration | Analogous | 40h | 10h | 50h |
| Testing | % of Dev | 40h | 8h | 48h |
| Documentation | Parametric | 16h | 4h | 20h |
| **Subtotal** | | **156h** | **34h** | **190h** |
| Management Overhead | 10% | | | 19h |
| **Total** | | | | **209h** |

Estimation Accuracy

Cone of Uncertainty

Estimate accuracy improves as project progresses:

PhaseAccuracy Range
Initial concept0.25x - 4x
Approved project0.5x - 2x
Requirements complete0.67x - 1.5x
Detailed design0.8x - 1.25x
Code complete0.9x - 1.1x

Implication: Early estimates need wider ranges; refine as knowledge grows.

Estimation Levels

LevelAccuracyWhen Used
ROM (Rough Order of Magnitude)-25% to +75%Initial budgeting
Budget-10% to +25%Project approval
Definitive-5% to +10%Execution baseline

Common Pitfalls

PitfallPrevention
Single-point estimatesAlways provide ranges
Optimism biasUse historical data, add contingency
AnchoringEstimate before seeing others' estimates
Planning fallacyInclude realistic overhead and risks
Scope creepDocument assumptions, re-estimate on changes
Precision theaterMatch precision to actual knowledge

Integration

Upstream

  • Requirements - What to estimate
  • risk-analysis - Risks affecting estimates
  • stakeholder-analysis - Who needs estimates, precision required

Downstream

  • Project planning - Resource allocation, scheduling
  • Budgeting - Cost forecasting
  • prioritization - Cost input for value/effort analysis

Related Skills

  • risk-analysis - Risks affecting estimates
  • prioritization - Using estimates for prioritization
  • decision-analysis - Trade-off decisions
  • value-stream-mapping - Estimating process improvement effort

Version History

  • v1.0.0 (2025-12-26): Initial release

平台分布

Antigravity

28.52%
按下载量换算108

Claude Code

22.15%
按下载量换算84

Gemini CLI

19.22%
按下载量换算73

Codex

12.63%
按下载量换算48

OpenCode

7.27%
按下载量换算28

trae

3.54%
按下载量换算13

安全审计

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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。

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