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test-effort-estimator测试工作量估计器

Agent Skill

用于辅助测试设计、自动化测试、用例整理和回归验证。它适合让 Agent 编写单元测试、端到端测试、测试计划或根据失败日志定位问题。使用时需要确认项目测试框架、运行命令和夹具数据,避免为了通过测试而改坏真实逻辑;涉及浏览器或外部服务时,应区分本地模拟、测试环境和生产环境。

总安装

8,776

周安装

355

GitHub Stars

1

下载量

2,755
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:test-effort-estimator(测试工作量估计器)
来源仓库:https://github.com/xuping2012/test-effort-estimator
安装命令:
openclaw skills install test-effort-estimator
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install test-effort-estimator

简介

test-effort-estimator 用于根据产品需求估算测试工作量,辅助项目排期。

  • 可分解任务并分析复杂度,输出合理工时评估。
  • 支持多维度指标计算,如用例数量与自动化比例。
  • 安装命令为 openclaw skills install test-effort-estimator,需输入详细需求描述。
  • 建议结合历史数据校准模型,提高预估准确性。

SKILL.md

name
test-effort-estimator
description
This skill should be used when users need to estimate test effort based on product requirements. It analyzes requirements, breaks down tasks, estimates test effort (case design, first run, retest, regression), and exports results to Excel.

Test Effort Estimator

Purpose

This skill provides a systematic approach to estimate test effort based on product requirements. It analyzes requirements, breaks them down into testable items, estimates effort for each phase (case design, first run, retest, regression), and generates an Excel report.

When to Use

Use this skill when users provide product requirements and need:

  • Test effort estimation for new features
  • Resource planning for testing phases
  • Detailed breakdown of testing activities
  • Excel export of effort estimates

How to Use

Step 1: Analyze Requirements

Read and understand the provided product requirements. Identify:

  • Functional modules and features
  • User stories and test scenarios
  • Complexity levels of different features

Step 2: Break Down Test Items

For each requirement, identify test items:

  • Test entry points and navigation
  • Data display and validation
  • User interactions and workflows
  • System operations and state changes

Step 3: Estimate Effort

Apply complexity-based estimation standards:

Simple Features (0.20-0.30 person-days for design):

  • Single function, clear logic
  • Few operation steps, simple data preparation
  • Examples: list display, simple navigation

Medium Features (0.35-0.40 person-days for design):

  • Multiple sub-functions, moderate complexity
  • Requires test data preparation
  • Examples: data filtering, user management

Complex Features (0.50 person-days for design):

  • Complex business logic, multiple interaction paths
  • Requires diverse test data, strong dependencies
  • Examples: online/offline binding, batch operations

Time Calculation Formulas:

  • Case Design: Simple 0.20-0.30, Medium 0.35-0.40, Complex 0.50
  • First Run: Simple 0.15-0.20, Medium 0.25-0.30, Complex 0.30-0.40
  • Retest: 33%-67% of first run, round to 0.10 minimum
  • Regression: 48%-67% of first run, round to two decimals

Step 4: Generate Excel Report

Use the bundled script scripts/generate_excel.py to create the Excel report with:

  • Requirement title
  • Requirement story/description
  • Case design time
  • First run time
  • Retest time
  • Regression time
  • Estimation rationale

Constraints

  • All time values must be >= 0.10 person-days
  • All time values must be rounded to two decimals
  • Total estimation error should be within 0.5 person-days of actual values
  • Minimum unit is 0.01 person-days

Bundled Resources

Scripts

  • scripts/generate_excel.py: Python script to generate Excel report from estimation data

References

  • references/complexity-standards.md: Detailed complexity classification criteria and examples
  • references/estimation-formulas.md: Complete formula documentation and calculation examples

Workflow

  1. Load complexity standards from references/complexity-standards.md
  2. Analyze requirements and identify test items
  3. Apply estimation formulas based on complexity
  4. Execute scripts/generate_excel.py to generate Excel report
  5. Review and validate total estimates against constraints

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

94.44%
按下载量换算2,602

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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