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skillify

Turn a repeatable workflow from the current session into a reusable OMC skill draft

skillify 是什麼?

skillify is a Claude Code agent skill that turn a repeatable workflow from the current session into a reusable OMC skill draft.

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

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說明文件

skillify 是做什麼的?

Use this skill when the current session uncovered a repeatable workflow that should become a reusable OMC skill.

Goal

Capture a successful multi-step workflow as a concrete skill draft instead of rediscovering it later.

Quality Gate

Before extracting a skill, all three should be true:

  • "Could someone Google this in 5 minutes?" → No.
  • "Is this specific to this codebase, project, or workflow?" → Yes.
  • "Did this take real debugging, design, or operational effort to discover?" → Yes.

Prefer skills that encode decision-making heuristics, constraints, pitfalls, and verification steps. Avoid generic snippets, boilerplate, or library usage examples that belong in normal documentation.

Workflow

  1. Identify the repeatable task the session accomplished.
  2. Extract:
    • inputs
    • ordered steps
    • success criteria
    • constraints / pitfalls
    • verification evidence
    • best target location for the skill
  3. Decide whether the workflow belongs as:
    • a repo built-in skill
    • a user/project learned skill
    • documentation only
  4. When drafting a learned skill file, output a complete skill file that starts with YAML frontmatter.
    • Never emit plain markdown-only skill files.
    • Do not write plain markdown without frontmatter.
    • Minimum frontmatter:
      ---
      name: <skill-name>
      description: <one-line description>
      triggers:
        - <trigger-1>
        - <trigger-2>
      ---
      
    • Write learned/user/project skills to flat file-backed paths:
      • ${CLAUDE_CONFIG_DIR:-~/.claude}/skills/omc-learned/<skill-name>.md
      • .omc/skills/<skill-name>.md
    • Remember that uncommitted skills are still worktree-local until committed or copied to a user-level directory.
  5. Draft the rest of the skill file with clear triggers, steps, success criteria, and pitfalls.
  6. Point out anything still too fuzzy to encode safely.

Rules

  • Only capture workflows that are actually repeatable.
  • Keep the skill practical and scoped.
  • Prefer explicit success criteria over vague prose.
  • If the workflow still has unresolved branching decisions, note them before drafting.
  • Keep omc-learned as the storage directory name for compatibility; do not present it as the public invocation name.

Output

  • Proposed skill name
  • Target location
  • Draft workflow structure or complete skill file
  • Verification or quality-gate notes
  • Open questions, if any

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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