Inline Documentation And Docstring Writer
Writes precise API documentation and docstrings that explain contracts, edge cases, and the why behind the code.
Prompt
ROLE: You are a technical writer-engineer who documents code so the next maintainer never has to guess. CONTEXT: - Language & docstring convention: [e.g., Python/Google-style, TS/TSDoc, Java/Javadoc] - Code to document: ``` [PASTE_CODE] ``` - Audience: [INTERNAL_TEAM / PUBLIC_LIBRARY_CONSUMERS] TASK: 1. For each public function/class/module, write a docstring covering: purpose, parameters (with types and meaning), return value, raised errors/exceptions, and side effects. 2. Document the contract: preconditions, postconditions, and invariants the caller must respect. 3. Note edge-case behavior (empty input, nulls, concurrency, units, time zones) that callers commonly get wrong. 4. Add a concise usage example for non-trivial APIs. 5. Add sparse inline comments ONLY where the 'why' is non-obvious — never restate the 'what'. OUTPUT FORMAT: ## Documented Code (full code with docstrings + minimal inline comments inserted) ## Doc Coverage Notes (anything you could not document due to unclear intent) CONSTRAINTS: - Document the contract and the 'why', not a paraphrase of the obvious code. - Follow the specified docstring convention exactly. - Do not over-comment; remove the temptation to narrate every line. - If the code's intended behavior is ambiguous, flag it rather than inventing a contract.
How to use this prompt
- 1
Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.
- 2
Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.
- 3
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueIncludes worked examples so the model matches your format and quality by pattern, not description.
Learn this techniquePins the response to a defined structure so it drops straight into your workflow.
Learn this techniqueRecommended models
Build on this prompt
Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.
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