prompt-refiner

Refines vague coding requests into execution-ready prompts for other coding agents.

Updated May 20, 2026
One-click install
npx skills add https://github.com/TeXmeijin/agent-skills --skill prompt-refiner-texmeijin
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: prompt-refiner
Source: https://github.com/TeXmeijin/agent-skills/tree/main/.apm/skills/prompt-refiner
Command: npx skills add https://github.com/TeXmeijin/agent-skills --skill prompt-refiner-texmeijin

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Rough, vague, or frustrated implementation requests often cause coding agents to produce lazy or incorrect work. This Skill turns under-specified requests into well-grounded, copy-paste-ready prompts by verifying facts first and structuring only what matters. ## Core Features & Use Cases - Pre-investigation Pass: Verifies static facts before writing — files, symbols, GitHub Issues/PRs via gh, configs, and dates — so the refined prompt stands on confirmed evidence, not guesses. - Structured Prompt Output: Produces prompts with Background, Facts, Task, Ideal outcome, and Done condition, plus optional Constraints, Assumptions, and Open Questions. - Lazy-work Guardrails: Strengthens done conditions when a request is likely to produce shallow answers, and requires comparison when multiple solution paths exist. - Use Case: You type "the login flow is broken, fix it" — the Skill checks the actual auth code and related issues, then outputs a precise prompt with file:line references and a clear completion criterion for the next agent. ## Quick Start Ask the agent to refine your rough coding request into a prompt for another coding agent, pasting in your original request as-is.

Frequently Asked Questions about prompt-refiner

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I turn a vague coding request into a good prompt for an AI agent?▼

Provide your rough request and let the refinement pass verify referenced files, symbols, and GitHub issues first. The output is a copy-paste-ready prompt containing background, confirmed facts, the task, ideal outcome, and a done condition.

What should a prompt for a coding agent include?▼

A reliable coding-agent prompt includes background, verified facts with sources like file:line or PR numbers, a clear task, the ideal outcome, and a done condition. Add constraints, assumptions, and open questions only when they reduce ambiguity.

Does prompt refinement require access to my repository?▼

Repository access improves results because the pre-investigation pass confirms files, symbols, and configs actually exist. If you ask to skip investigation, the Skill honors that but marks unverified items as assumptions or open questions.

When should I not use a prompt-refining step?▼

Skip refinement for trivial, well-specified tasks where extra structure adds no value, or when you explicitly want the request passed through as-is. The Skill keeps small tasks small and only adds structure when risk or ambiguity is high.

Why do coding agents give lazy answers to short prompts?▼

Short prompts lack verified facts and completion criteria, so agents guess or stop early. Strengthening the done condition and grounding the task in confirmed file references forces more thorough execution.