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Yeachan-Heo/external-context

Yeachan-Heo

external-context

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

global
0installs0uses~522
v1.1Saved Apr 20, 2026

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
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Overall Score

72/100

Grade

B

Good

Safety

78

Quality

68

Clarity

75

Completeness

62

Summary

External Context is a meta-skill that decomposes user queries into 2-5 independent search facets and spawns parallel document-specialist Claude agents to fetch external documentation and web references. It synthesizes results into a structured report with citations.

Detected Capabilities

Query decomposition and facet extractionParallel agent invocation via Task toolWeb search and documentation fetching (delegated to subagents)Result synthesis and citation aggregationStructured markdown output generation

Trigger Keywords

Phrases that MCP clients use to match this skill to user intent.

research best practicescompare frameworksexternal documentation lookupgather technical referenceslatest patterns and conventions

Risk Signals

INFO

Invokes external document-specialist agents via Task tool with model specification and web search prompts

Step 2: Parallel Agent Invocation
INFO

Delegates WebSearch and WebFetch to subagents — no direct network control in this skill

Step 2: Parallel Agent Invocation
WARNING

No validation or sanitization of user query before facet decomposition

Step 1: Facet Decomposition
WARNING

Maximum 5 parallel agents cap documented but no error handling for subagent failures

Configuration section

Use Cases

  • Research best practices for a technology or pattern
  • Compare competing frameworks or libraries
  • Find latest conventions and patterns for a technology
  • Gather multi-perspective external documentation on a topic
  • Aggregate technical references from official sources

Quality Notes

  • Clear protocol structure with three well-defined steps (decomposition, invocation, synthesis)
  • Good use of code blocks and markdown formatting for readability
  • Examples are concrete and illustrative of intended use cases
  • Output format is well-specified with section headers and citation requirements
  • Missing error handling guidance: what happens if a document-specialist agent times out or fails?
  • No guidance on how to choose facet count (2-5 range is wide) or what makes a good facet
  • No limitation documentation on query complexity, query length, or types of queries to avoid
  • Configuration section is minimal — does not document model selection rationale, timeout behavior, or retry logic
  • No edge case coverage: how to handle queries with no search results, ambiguous queries, or proprietary/closed-source topics
  • Facet decomposition guidance is vague ('Search focus: What to search for') — would benefit from concrete heuristics
Model: claude-haiku-4-5-20251001Analyzed: Apr 20, 2026

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Version History

v1.1

Content updated

2026-04-20

Latest
v1.0

No changelog

2026-04-12

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