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.
npx skills add ZTE-AICloud/Co-OmniSpec --skill e2e-designgit clone --depth 1 https://github.com/ZTE-AICloud/Co-OmniSpecWrote 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.
[](https://agentmods.dev/skills/zte-aicloud/co-omnispec/e2e-design)<a href="https://agentmods.dev/skills/zte-aicloud/co-omnispec/e2e-design"><img src="https://agentmods.dev/badge/skills/zte-aicloud/co-omnispec/e2e-design/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.
<a href="https://agentmods.dev/skills/zte-aicloud/co-omnispec/e2e-design"><img src="https://agentmods.dev/badge/skills/zte-aicloud/co-omnispec/e2e-design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00094 | $0.02715 |
| Opus 5 | $0.00047 | $0.01358 |
| Sonnet 5 | $0.00019 | $0.00543 |
| Haiku 4.5 | $0.00009 | $0.00271 |
Grade A, and why
e2e-design 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 292 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
执行测试实现分析工作流,在黑盒测试用例基础上分析入口函数、外部依赖、测试数据、验证点,并复用存量测试设计。
调用场景:
- 初步设计(在
/design之后):基于设计文档和黑盒测试用例生成测试实现分析报告 - 独立调用:直接执行测试实现分析(需要已有 design.md 和 e2e-test.md)
输入要求:
spec.md:功能规范文档design.md:设计文档e2e-test.md:黑盒测试用例文档
输出:
e2e-impl-design.md:测试实现分析报告
执行流程
1. [ ] 设置环境
- 判断操作系统:Windows 或 Linux
- 运行前置检查脚本:
- Windows:
scripts/powershell/check-prerequisites.ps1 --json --require-design --require-e2e-test - Linux:
scripts/bash/check-prerequisites.sh --json --require-design --require-e2e-test
- Windows:
- 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
DESIGN_FILE(设计文件路径) - 提取
E2E_TEST_FILE(黑盒测试用例文件路径) - 提取
AVAILABLE_DOCS(可用文档列表)
- 提取
重要:所有路径必须是绝对路径。
2. [ ] 验证前置文件
验证以下必需文件是否存在:
-
检查规范文件:
{FEATURE_DIR}/spec.md是否存在- 如果不存在:错误 "规范文件不存在,请先执行 /specify"
-
检查设计文件:
{FEATURE_DIR}/design.md是否存在- 如果不存在:错误 "设计文件不存在,请先执行 /design"
-
检查测试用例文件:
{FEATURE_DIR}/e2e-test.md是否存在- 如果不存在:错误 "黑盒测试用例文件不存在,请先执行 /e2e-specify"
-
报告验证结果:
- 所有文件存在:继续执行步骤3
- 任何文件缺失:终止流程并报错
3. [ ] 加载上下文文档
加载用于测试实现分析的上下文文档:
必需文档:
- spec.md:读取用户故事、功能需求、验收场景
- design.md:读取架构设计、详细设计、接口定义、数据结构
- e2e-test.md:读取所有黑盒测试用例(Given-When-Then 格式)
可选文档(按优先级加载):
-
baseline 文档:
baseline/code-structure.md:现有代码结构baseline/existing-apis.md:现有接口定义
-
存量测试代码:
- 搜索现有测试目录(如
tests/、test/) - 查找类似功能的测试实现
- 提取测试范式、Mock 对象使用、测试数据构造方法
- 搜索现有测试目录(如
加载策略:
- 每个文档独立容错,失败不中断流程
- 记录成功加载的文档列表
- 标注缺失的文档
4. [ ] 启动测试实现分析 Agent
使用 Agent 工具启动 @"test-impl-design (agent)",传递以下参数:
Agent 参数:
subagent_type: "general-purpose"(使用通用 agent)description: "测试实现分析 - 生成测试实现分析报告"prompt包含以下内容:
# 测试实现分析任务
## 调用场景
{场景类型}: 初步设计/独立调用
## 输入文件
- spec.md: {SPEC_FILE}
- design.md: {DESIGN_FILE}
- e2e-test.md: {E2E_TEST_FILE}
- feature_dir: {FEATURE_DIR}
- baseline_docs: {成功加载的 baseline 文档列表}
- existing_tests: {找到的存量测试代码}
## 任务要求
1. 读取 spec.md、design.md、e2e-test.md
2. 分析每个黑盒测试用例的入口函数
3. 识别外部依赖并设计 Fake 对象
4. 设计测试数据(输入数据、Fake 数据)
5. 定义验证点(返回值、状态变化、可观察行为)
6. 分析存量测试复用可能性
7. 生成测试实现分析报告(e2e-impl-design.md)
## 输出位置
- e2e-impl-design.md: {FEATURE_DIR}/e2e-impl-design.md
## 重要说明
- 重点关注入口函数签名、外部依赖、测试数据
- 复用存量测试模式和测试工具
- 保持黑盒测试特性,不暴露内部实现
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.
- 11d ago First seen · 292 lines · 94 tokens per session scan A 61eeb99fcc12
e2e-design is a skill published in the GitHub repository ZTE-AICloud/Co-OmniSpec (54 stars, last pushed 1mo ago), licensed MIT. It adds 94 tokens to every session and 2,715 once invoked, about $0.0005 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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