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external-context

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

external-context とは?

external-context is a Claude Code agent skill that invoke parallel document-specialist agents for external web searches and documentation lookup.

対応Claude Code~Codex CLI~Cursor
npx skills add https://github.com/Yeachan-Heo/oh-my-claudecode/tree/main/skills/external-context

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ドキュメント

External Context Skill

Fetch external documentation, references, and context for a query. Decomposes into 2-5 facets and spawns parallel document-specialist Claude agents.

Usage

/oh-my-claudecode:external-context <topic or question>

Examples

/oh-my-claudecode:external-context What are the best practices for JWT token rotation in Node.js?
/oh-my-claudecode:external-context Compare Prisma vs Drizzle ORM for PostgreSQL
/oh-my-claudecode:external-context Latest React Server Components patterns and conventions

Protocol

Step 1: Facet Decomposition

Given a query, decompose into 2-5 independent search facets:

## Search Decomposition

**Query:** <original query>

### Facet 1: <facet-name>
- **Search focus:** What to search for
- **Sources:** Official docs, GitHub, blogs, etc.

### Facet 2: <facet-name>
...

Step 2: Parallel Agent Invocation

Fire independent facets in parallel via Task tool:

Task(subagent_type="oh-my-claudecode:document-specialist", model="sonnet", prompt="Search for: <facet 1 description>. Use WebSearch and WebFetch to find official documentation and examples. Cite all sources with URLs.")

Task(subagent_type="oh-my-claudecode:document-specialist", model="sonnet", prompt="Search for: <facet 2 description>. Use WebSearch and WebFetch to find official documentation and examples. Cite all sources with URLs.")

Maximum 5 parallel document-specialist agents.

Step 3: Synthesis Output Format

Present synthesized results in this format:

## External Context: <query>

### Key Findings
1. **<finding>** - Source: [title](url)
2. **<finding>** - Source: [title](url)

### Detailed Results

#### Facet 1: <name>
<aggregated findings with citations>

#### Facet 2: <name>
<aggregated findings with citations>

### Sources
- [Source 1](url)
- [Source 2](url)

Configuration

  • Maximum 5 parallel document-specialist agents
  • No magic keyword trigger - explicit invocation only

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

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

omc-doctor

Diagnose and fix oh-my-claudecode installation issues

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