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ALWAYS use this when the request matches Wiki QA: Answer repository questions grounded entirely in source code evidence.

Install

mkdir -p .claude/skills/wiki-qa-anhvu1107 && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/14866" && unzip -o skill.zip -d .claude/skills/wiki-qa-anhvu1107 && rm skill.zip

Installs to .claude/skills/wiki-qa-anhvu1107

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

ALWAYS use this when the request matches Wiki QA: Answer repository questions grounded entirely in source code evidence.
120 chars✓ has a “when” trigger

About this skill

Wiki Q&A

Selective Reading Rule

Start with:

  • references/senior-master-standard.md
  • references/usage-routing.md
  • references/quality-checklist.md

Then load only the inherited docs, scripts, assets, or examples that match the user's actual task.

Answer repository questions grounded entirely in source code evidence.

When to Use

  • User asks a question about the codebase
  • User wants to understand a specific file, function, or component
  • User asks "how does X work" or "where is Y defined"

Procedure

  1. Detect the language of the question; respond in the same language
  2. Search the codebase for relevant files
  3. Read those files to gather evidence
  4. Synthesize an answer with inline citations

Response Format

  • Use ## headings, code blocks with language tags, tables, bullet lists
  • Cite sources inline: (src/path/file.ts:42)
  • Include a "Key Files" table mapping files to their roles
  • If information is insufficient, say so and suggest files to examine

Rules

  • ONLY use information from actual source files
  • NEVER invent, guess, or use external knowledge
  • Think step by step before answering

When to Use

This skill is applicable to execute the workflow or actions described in the overview.

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

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