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Skillify(技能化)

将当前会话中可重复的工作流程转化为一个可复用的 OMC 技能草稿。

Skillify(技能化) 是什么?

Skillify 是一个用于提取和形式化开发者工作流中重复步骤的技能,适用于 Claude Code 等 AI 代理的 OMC(Open Multi-agent Coordination)环境。它通过识别、捕获和结构化多步骤任务(如调试、设计或操作流程),将其转化为可复用的技能文件,从而避免重复劳动。该技能支持输出为仓库内置技能、用户/项目学习技能或仅文档,并强制要求使用 YAML 前置元数据定义名称、描述和触发条件,确保文件的机器可读性。生成的技能文件可存储在 `omc-learned` 或 `.omc/skills/` 目录下,支持工作树本地或用户级持久化部署。Skillify 强调捕获决策启发式、约束、陷阱和验证步骤,而非通用代码片段或样板文件,适合需要深度定制和重复执行的场景。

兼容平台✓Claude Code~Codex CLI~Cursor
npx skills add https://github.com/Yeachan-Heo/oh-my-claudecode/tree/main/skills/skillify

在你喜欢的 AI 中提问

打开一个已预加载此 Agent Skill 的新对话。

文档

Skillify(技能化) 是做什么的?

当当前会话揭示了一个可重复的工作流程,且应将其转化为可复用的 OMC 技能时,使用此技能。

目标

捕获一个成功的多步骤工作流,将其作为具体的技能草稿,而非日后重新发现。

质量门禁

在提取技能之前,以下三条均需为真:

  • “有人能在5分钟内用谷歌搜到吗?” → 否。
  • “这个流程是否特定于此代码库、项目或工作流?” → 是。
  • “发现此流程是否经过了真正的调试、设计或操作努力?” → 是。

优先选择编码了决策启发式、约束条件、陷阱和验证步骤的技能。避免属于普通文档的通用代码片段、样板文件或库使用示例。

工作流程

  1. 识别会话完成的重复性任务。
  2. 提取:
    • 输入
    • 有序步骤
    • 成功标准
    • 约束条件/陷阱
    • 验证证据
    • 技能的最佳存放位置
  3. 确定该工作流属于以下哪种类型:
    • 仓库内置技能
    • 用户/项目学习技能
    • 仅作为文档
  4. 在起草学习技能文件时,输出一个完整的技能文件,以 YAML 前置元数据开头。
    • 切勿仅输出纯 Markdown 技能文件。
    • 禁止编写不带前置元数据的纯 Markdown。
    • 最低前置元数据要求:
      ---
      name: <技能名称>
      description: <一行描述>
      triggers:
        - <触发器1>
        - <触发器2>
      ---
      
    • 将学习/用户/项目技能写入基于平面文件的路径:
      • ${CLAUDE_CONFIG_DIR:-~/.claude}/skills/omc-learned/<技能名称>.md
      • .omc/skills/<技能名称>.md
    • 请记住,未提交的技能在提交或复制到用户级目录之前,仍局限于工作树。
  5. 起草技能文件的其余部分,明确触发器、步骤、成功标准和陷阱。
  6. 指出任何尚不明确、无法安全编码的内容。

规则

  • 仅捕获确实可重复的工作流。
  • 保持技能的实用性和范围明确。
  • 优先使用明确的成功标准,而非模糊的描述。
  • 如果工作流仍有未解决的分支决策,在起草前说明。
  • 将 omc-learned 保持为存储目录名称以保证兼容性;不要将其作为公开调用名称呈现。

输出

  • 建议的技能名称
  • 目标位置
  • 草稿工作流结构或完整技能文件
  • 验证或质量门禁说明
  • 开放问题(如有)

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

agent-doc-discipline

Writing-time discipline for documents agents consume (the five surfaces, specs, tickets, .omc/skills/) — every rule checkable and carrying a why, steps before reference, one meaning in one home, no restating what the environment already says. Mandatory at drydock seed generation and the launch C5 sediment pass; opt-in for any other agent-facing doc edit. The companion of minimal-code-discipline: that one disciplines code, this one disciplines papers.

ai-slop-cleaner

Clean AI-generated code slop with a regression-safe, deletion-first workflow and optional reviewer-only mode

ask

Process-first advisor routing for Claude, Codex, Gemini, Antigravity, Grok, or Cursor via `omc ask`, with artifact capture and no raw CLI assembly

ask-navigator

Shipyard

autopilot

Full autonomous execution from idea to working code

autoresearch

Stateful single-mission improvement loop with strict evaluator contract, markdown decision logs, and max-runtime stop behavior

cancel

Cancel any active OMC mode (autopilot, ralph, ultragoal, swarm, ultrapilot, pipeline, team) and clean up retired legacy state

configure-notifications

Configure notification integrations (Telegram, Discord, Slack) via natural language

debug

Diagnose the current OMC session or repo state using logs, traces, state, and focused reproduction

deepinit

Deep codebase initialization with hierarchical AGENTS.md documentation

deep-interview

Socratic deep interview with mathematical ambiguity gating before explicit execution approval

drydock

Lay the keel of the shipyard harness in any repo — the 4-pillar shared environment (Context, Rules, Tools, Standards) across 5 surfaces (CLAUDE.md, skills, design-system, mcp/cli, shared context) so that every human and agent inherits the same design language and anyone can ship. Run once per repo; re-run with --check to audit drift.

execute

Carry an approved task through to working, verified code

external-context

Invoke parallel document-specialist agents for external web searches and documentation lookup

graph

Deterministic orchestration graph runtime - declarative DAG pipelines with journal-based crash recovery

harbor

Harbor intake for external work — the captain only handles unresolved decisions. Sweeps incoming issues and PRs, verifies every claim before disposition, reuses every decision already made, and hands the maintainer a docket whose pending items each carry one question with options, recommendation, impact and evidence. Agent-autonomous for facts and for actions covered by standing authorization; signed for every new judgment. Never merges.

hud

Configure HUD display options (layout, presets, display elements)

launch

Shipyard

loft

Loft the shape before cutting steel — answer a design question that prose cannot settle by building a throwaway artifact: a pure logic module in a clickable shell, or structurally different UI variants behind one route. The captain reacts to the artifact; the answer folds into the decision; the artifact never docks. Use when a design question stalls in words, when a navigator map carries a loft ticket, or when a spec discussion reaches

minimal-code-discipline

YAGNI-ladder coding discipline for writing changes — existence-first, reuse before writing, dependency ladder, shortest correct diff, with non-negotiables that must never be minimized away

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