wiki-qa

Answer repository questions grounded entirely in source code evidence. Use when user asks a question about the codebase, user wants to understand a specific file, function, or component, or user asks "how does X work" or "where is Y defined".

31,392 stars

Best use case

wiki-qa is best used when you need a repeatable AI agent workflow instead of a one-off prompt. It is especially useful for teams working in multi. Answer repository questions grounded entirely in source code evidence. Use when user asks a question about the codebase, user wants to understand a specific file, function, or component, or user asks "how does X work" or "where is Y defined".

Answer repository questions grounded entirely in source code evidence. Use when user asks a question about the codebase, user wants to understand a specific file, function, or component, or user asks "how does X work" or "where is Y defined".

Users should expect a more consistent workflow output, faster repeated execution, and less time spent rewriting prompts from scratch.

Practical example

Example input

Use the "wiki-qa" skill to help with this workflow task. Context: Answer repository questions grounded entirely in source code evidence. Use when user asks a question about the codebase, user wants to understand a specific file, function, or component, or user asks "how does X work" or "where is Y defined".

Example output

A structured workflow result with clearer steps, more consistent formatting, and an output that is easier to reuse in the next run.

When to use this skill

  • Use this skill when you want a reusable workflow rather than writing the same prompt again and again.

When not to use this skill

  • Do not use this when you only need a one-off answer and do not need a reusable workflow.
  • Do not use it if you cannot install or maintain the related files, repository context, or supporting tools.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/wiki-qa/SKILL.md --create-dirs "https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/plugins/antigravity-awesome-skills-claude/skills/wiki-qa/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/wiki-qa/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How wiki-qa Compares

Feature / Agentwiki-qaStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Answer repository questions grounded entirely in source code evidence. Use when user asks a question about the codebase, user wants to understand a specific file, function, or component, or user asks "how does X work" or "where is Y defined".

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# Wiki Q&A

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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