e2e-specify

e2e-specify is a skill for Claude Code from ZTE-AICloud/Co-OmniSpec. It costs 121 tokens per session (1,531 once invoked), scanned A, original, MIT.

A test-analysis and test-case design workflow for turning a software specification into a test report and black-box test cases. Black-box tests check a system through its inputs and outputs without relying on its internal code.

In plain words
What is it for?
Use it to analyze requirements, design end-to-end tests, and create test documents for a new or updated feature.
Why use it?
It helps reveal missing test points and gives testers concrete cases to run after requirements are written or clarified.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Part of the omni-dsdd plugin — 40 skills, 16 agents, 1 hook shipped together

Good fit Use it to analyze requirements, design end-to-end tests, and create test documents for a new or updated feature.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/zte-aicloud/co-omnispec/e2e-specify
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add ZTE-AICloud/Co-OmniSpec --skill e2e-specify
Clone the repo
git clone --depth 1 https://github.com/ZTE-AICloud/Co-OmniSpec

Made for: Claude Code.

Or install omni-dsdd, the plugin that ships this one along with the rest of its 40 skills, 16 agents, 1 hook.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for e2e-specify

README.md
[![agentmods](https://agentmods.dev/badge/skills/zte-aicloud/co-omnispec/e2e-specify/github.svg)](https://agentmods.dev/skills/zte-aicloud/co-omnispec/e2e-specify)
Your own site
<a href="https://agentmods.dev/skills/zte-aicloud/co-omnispec/e2e-specify"><img src="https://agentmods.dev/badge/skills/zte-aicloud/co-omnispec/e2e-specify/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for e2e-specify

Your own site · 80×15
<a href="https://agentmods.dev/skills/zte-aicloud/co-omnispec/e2e-specify"><img src="https://agentmods.dev/badge/skills/zte-aicloud/co-omnispec/e2e-specify.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 121 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,531 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00121 $0.01531
Opus 5 $0.00060 $0.00766
Sonnet 5 $0.00024 $0.00306
Haiku 4.5 $0.00012 $0.00153

Measured 9d ago against content hash ea01cf6402ab, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

e2e-specify scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

omni-dsdd/skills/e2e-specify/SKILL.md · 167 lines

How it starts

The opening of the file, as written. The whole thing — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.

用户输入

$ARGUMENTS

在继续之前, 你必须考虑用户输入(如果不为空).

概述

执行测试分析与设计工作流,使用 MFQ&PPDCS 方法论进行测试分析,然后使用 TCON 方法设计黑盒测试用例。

调用场景

  1. 初步设计(在 /specify 之后):基于初始规范生成初步测试分析和设计
  2. 更新设计(在 /clarify 之后):基于澄清后的规范更新测试分析和设计

执行流程

1. [ ] 设置环境

  1. 判断操作系统:Windows 或 Linux
  2. 运行前置检查脚本
    • Windows: scripts/powershell/check-prerequisites.ps1 --json
    • Linux: scripts/bash/check-prerequisites.sh --json
  3. 解析输出
    • 提取 FEATURE_DIR(特性目录绝对路径)
    • 提取 SPEC_FILE(规范文件路径)
    • 提取 AVAILABLE_DOCS(可用文档列表)

重要:所有路径必须是绝对路径。

2. [ ] 确定调用场景

根据调用上下文确定场景类型:

  • 初步设计:如果在 /specify 之后调用,场景为"初步设计"
  • 更新设计:如果在 /clarify 之后调用,场景为"更新设计"

3. [ ] 启动测试分析设计 Agent

使用 Agent 工具启动 @"test-analysis-design (agent)",传递以下参数:

Agent 参数

  • subagent_type: "general-purpose"(使用通用 agent)
  • description: "测试分析与设计 - 生成测试分析和黑盒测试用例"
  • prompt 包含以下内容:
# 测试分析与设计任务

## 调用场景
{场景类型}: 初步设计/更新设计

## 输入文件
- spec.md: {SPEC_FILE}
- feature_dir: {FEATURE_DIR}

## 任务要求
1. 读取 spec.md 规范文件
2. 使用 MFQ&PPDCS 方法论进行测试分析
3. 生成测试分析报告(test-analysis.md)
4. 使用 TCON 四步法设计黑盒测试用例
5. 生成黑盒测试用例文档(e2e-test.md)

## 输出位置
- test-analysis.md: {FEATURE_DIR}/test-analysis.md
- e2e-test.md: {FEATURE_DIR}/e2e-test.md

## 重要说明
- 如果是"初步设计"场景:所有 Issues 保持 Open 状态
- 如果是"更新设计"场景:根据澄清结果更新,将相关 Issues 标记为 Resolved

4. [ ] 验证生成文档

等待 agent 完成后,验证生成的文档:

  1. 检查文档存在性

    • 检查 {FEATURE_DIR}/test-analysis.md 是否存在
    • 检查 {FEATURE_DIR}/e2e-test.md 是否存在
  2. 验证文档内容

    • test-analysis.md 应包含:
      • KYM 分析
      • TCO 分析
      • MFQ 建模结果
      • 测试点清单
      • Issues 列表(状态应为 Open 或 Resolved)
    • e2e-test.md 应包含:
      • 用例清单
      • 用例详情(Given-When-Then 格式)
      • 测试数据设计
      • 追溯性矩阵
  3. 处理验证结果

    • [成功] 验证成功:输出完成报告,继续下一步
    • [失败] 验证失败
      • 记录错误信息
      • 如果是关键错误(文档未生成、内容为空),报告失败
      • 如果是非关键错误(部分内容缺失),记录警告但继续

5. [ ] 报告完成情况

输出完成报告,包括:

  • 生成文档

    • test-analysis.md 路径
    • e2e-test.md 路径
  • 验证结果

    • 文档存在性检查:[成功]/[失败]
    • 内容完整性检查:[成功]/[失败]
    • 问题列表(如有)

Read the full file on GitHub · 167 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 167 lines · 121 tokens per session scan A ea01cf6402ab

Subscribe to this mod's changes

e2e-specify is a skill published in the GitHub repository ZTE-AICloud/Co-OmniSpec (54 stars, last pushed 1mo ago), licensed MIT. It adds 121 tokens to every session and 1,531 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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