external-context

External Context Skill

Fetch external documentation, references, and context for a query. Uses Gemini MCP as the preferred path (single call, 1M context window); falls back to parallel document-specialist Claude agents when MCP is unavailable.

Overview

1. Preferred: Gemini MCP - Single ask_gemini call with agent_role="document-specialist" handles multi-facet synthesis in one shot
2. Fallback: Parallel agents - Decompose into 2-5 facets, spawn 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 0: Discover MCP Tools

Before first MCP use, call ToolSearch("mcp") to discover deferred MCP tools. If results include ask_gemini, use the Preferred path. If no MCP tools are found, use the Fallback path.

---

Preferred Path: Gemini MCP

When: ToolSearch("mcp") returns ask_gemini.

1. Write the query to a prompt file:

.omc/prompts/ext-context-{timestamp}.md

Prompt file contents:

Search the web for external documentation, examples, and references on the following query:

**Query:** <original query>

Cover all relevant facets (up to 5). For each facet:
- Cite all sources with URLs
- Summarize key findings
- Note any version/date caveats

Output format:
## External Context: <query>

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

### Detailed Results

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

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

2. Call ask_gemini with background execution:

ask_gemini(
    agent_role="document-specialist",
    prompt_file=".omc/prompts/ext-context-{timestamp}.md",
    output_file=".omc/prompts/ext-context-{timestamp}-output.md",
    background=True
)

3. Wait for completion:

wait_for_job(job_id=<returned job id>)

4. Read the output file and present synthesized results to the user.

---

Fallback Path: Parallel Document-Specialist Agents

When: ToolSearch("mcp") returns no MCP tools (Gemini unavailable).

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>
...

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.

---

Synthesis Output Format

Regardless of path used, present 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 (fallback path)
• Gemini handles multi-facet synthesis in one shot (preferred path)
• No magic keyword trigger - explicit invocation only