精选
为什么选中它
待人工精选——以下事实来自源码仓库。
它能做什么
Generate Function, MCP, Agent Skill, and offline test packages from existing code; installable as a DeepSeek Harness bundle.
适合谁
想用 DSH 获得这项能力的用户;装前建议先看源码和文档。
风险提示
- 未发现明显风险信号;安装前仍建议查看源码。
Generate Function, MCP, Agent Skill, and offline test packages from existing code; installable as a DeepSeek Harness bundle.
待人工精选——以下事实来自源码仓库。
Generate Function, MCP, Agent Skill, and offline test packages from existing code; installable as a DeepSeek Harness bundle.
想用 DSH 获得这项能力的用户;装前建议先看源码和文档。
dsh plugin --profile web add github:leechen298/Code2Skill 作者没有声明支持的平台。
English | 简体中文 Code2Skill is a collection of installable Agent Skills that helps coding agents understand business functionality in user-authorized frontend, backend, or full-stack source code, then generate Functions, MCP tools, workflow Skills, and offline tests for other agents to use. Current release: v1.1.3. text Existing application code ↓ Code2Skill Functions + MCP Tools + Skills + Tests ↓ An agent gathers the required information and completes the user's goal Functions and MCP tools provide business capabilities. Skills guide an agent in using those capabilities. The consuming agent still decides whether to call a tool, what to clarify, how to interpret a response, and what to do next. ## What It Does - Generates capabilities from business invocation points that actually exist in source code. Client-backed features start from calls made by the client or consumer; projects without a client start from user-specified public APIs, RPCs, services, messages, or task entry points and follow their public request, response, and contract types as needed. - Identifies independently completable goals within a user-specified page, directory, feature, or public entry point. - Places field provenance, selected-record handoffs between tools, request assembly, and deterministic transformations in Functions. - Generates a Skill for each primary goal while reusing the necessary Functions and MCP tools. - Defaults to offline technical validation and does not call live business APIs. ## Supported Agents You can run Code2Skill with mainstream coding agents such as Codex, Claude Code, and Kimi Code. Generated Skills can be installed in Codex, Claude Code, Cursor, OpenClaw, and other environments that support Agent Skills. See the skills CLI compatibility list for more environments. To perform live business operations, register the generated MCP server as described in each package's MCP-SETUP.md. ## Installation Install all three Skills with the standard Agent Skills CLI: bash npx skills add leechen298/Code2Skill \ --skill code2skill-generate code2skill-review-flow code2skill-review-source \ --agent "$AGENT_ID" \ --global \ --yes - code2skill-generate: generates Functions, MCP tools, workflow Skills, and offline tests. - code2skill-review-flow: checks whether a user can complete the main goals through the generated workflows. - code2skill-review-source: reviews request fields, transformations, and invocation chains against the authorized source code. Routine generation only requires code2skill-generate. Run the two review Skills independently when needed. See the installation guide for migration from older versions, generated-package dependencies, and MCP registration. The detailed documentation is currently written in Chinese. ### DeepSeek Harness DeepSeek Harness users can install the three Skills as a Bundle in a selected profile: bash dsh plugin --profile web add github:leechen298/Code2Skill#v1.1.3 See the DeepSeek Harness integration guide for installation, verification, headless profiles, and removal. Generated business MCP servers must still be registered separately according to their own MCP-SETUP.md files. ## Usage Boundaries Code2Skill produces runnable, editable first drafts of business capabilities. It does not prove that every business rule or real environment has been validated. Results depend on the generation model, source completeness, and the scope the user authorizes. For complex writes or high-value workflows, review cross-tool data provenance, same-name field semantics, deterministic request transformations, goal-specific prerequisites, attachment uploads, and downstream bindings. Use code2skill-review-flow to check the main workflow and code2skill-review-source to inspect critical source semantics. Offline tests do not replace real API or deployment acceptance. ## Quick Start Invoke the generation Skill inside the target repository and explicitly authorize the source roots it may inspect: text Use $code2skill-generate to turn <page, directory, feature path, or public entry point> into runnable Functions, MCP tools, and Skills. Authorized source roots: <frontend>, <backend>, <protocol>, and <service/message/task directories>. Use invocation points that actually exist in source code as the capability source. Do not call live business APIs. For independent reviews: text Use $code2skill-review-flow to review whether the primary goals in <generated package path> can be completed. Use $code2skill-review-source to review whether <specific Skill or capability> in <generated package path> matches the authorized source code. ## Generated Package The logical output stays consistent while file extensions, dependencies, and startup commands follow the target stack's runtime profile. The current core-export-v1 default is implemented by the node-stdio profile: text generated/code2skill/<feature-id>/ ├── SKILL.md or skills/*/SKILL.md ├── function-core/index.mjs # node-stdio profile example ├── mcp-tool/index.mjs # node-stdio profile example ├── portable-agent-result.mjs # helper for HTTP scenarios ├── tests/ ├── package.json ├── MCP-SETUP.md └── references/feature-context.md # generated only when business context needs it Each generated MCP-SETUP.md records the runtime language, dependency installation, startup command, environment variables, unmet prerequisites, and MCP registration steps. A Skill being installed, an MCP server being connected, and the live business workflow being validated are three separate states. ## Generation Results Three runs against the same anonymized, multi-goal source package: | Generation model / configuration | Date | Generation time | Composite reference score | |---|---|---:|---:| | GPT-5.6 Sol (Ultra) | 2026-07-24 | 47m 45s | 9.4 | | Kimi K3 (Max reasoning) | 2026-07-24 | about 93m | 8.9 | | GPT-5.6 Sol (High) | 2026-07-24 | 20m 29s | 8.4 | Timing ends when generation and that run's offline validation finish; it excludes later scoring, directory cleanup, installation, and deployment. See the evaluation report for the two scoring systems, methodology, and privacy boundaries. The report is currently written in Chinese. ## Documentation - Install Skills, generated dependencies, and MCP servers (Chinese) - Generated package structure and design principles (Chinese) - Runtime-neutral generation design (Chinese) - Optional advanced validation (Chinese) - Models, scoring, and anonymized evaluation results (Chinese) - Full documentation index (Chinese) The Skills follow the Agent Skills specification and use vercel-labs/skills for installation. Generated MCP servers use standard stdio or Streamable HTTP transport.不看 Star,人工一条条挑的。
把 DSH 的 settings.yaml 做成可视化看板:所有已注册的 settings namespace——包括官方界面从未覆盖的第三方插件配置——都渲染成可编辑表单。项目还早,但方向很对:告别手改 YAML。
给 DSH 的 DIY 轨迹可视化:把 agent 的计划与执行画成图,不用翻原始日志也能看清它在干嘛。项目还早,但补上了「一眼看懂 agent 在做什么」这个真实缺口。
从 Claude Code / Codex 把活派给 DSH:在宿主内拉起带分级预设的 DSH agent 会话,看原生子代理进度,还能借它的多模态桥给纯文本的 DSH 补上视觉和生图。编排型插件,把 DSH 变成其他编码 agent 的后端。