prompt-spec-engineer (support Auto rewrite prompt)

Name: prompt-spec-engineer (support Auto rewrite prompt)
Price: 5 USD
Availability: InStock
Author: Agensi

by Roy Yuen

Turn vague prompts into professional task specifications, optimized prompts, and verification test suites.

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See it in action

You say

Create an optimized prompt and verification plan for an AI automation agency consultant to perform client audits using draft notes and tool lists.

Your agent does

Optimized Prompt: [System: AI Audit Expert] Act as a consultant for [User]. Use provided intake form to identify 3 workflow pain points. Verification Plan:

Source Grounding: Does output cite intake form?
JSON Contract: Validate keys [summary, risks, steps]. Test Cases generated: 5.

What you get

Convert rough drafts into professional-grade LLM instructionsGenerate structured JSON output contracts for consistent API responsesCreate automated test cases and review checklists for prompt QAScaffold Mesh Flow project.yaml files for AI agent orchestrationAudit existing prompts for noise, vague language, and missing constraints

About this skill

What it does

The Prompt Spec Engineer is a high-performance utility designed for developers, agencies, and AI builders who need to move beyond "vibes-based" prompting. It transforms vague, bloated, or noisy prompts into rigorous, outcome-first task specifications and optimized prompt packs.

Instead of relying on fuzzy instructions, this skill applies an engineering mindset to prompt design. It diagnoses prompt quality, strips low-signal filler, identifies missing requirements, and generates a full suite of deployment artifacts including Markdown specs, JSON contracts, and YAML orchestration flows.

Supported Tools & Frameworks

Mesh Flow: Generates project.yaml for orchestration.
CLI Integration: Supports structured JSON intake and automated directory-based output.
Multi-Format Output: Produces Markdown, JSON, CSV (test cases/checklists), and YAML.

Why use this skill?

Prompting is often treated as a trial-and-error process. This skill automates the "boring part" of prompt engineering—validation, test case generation, and contract definition—ensuring your prompts are production-ready and verifiable. Unlike manual prompting, it is deterministic and evidence-based, citing specific source material for every constraint and requirement it generates.

Output

You receive a complete "Prompt Pack" comprising an optimized prompt, a functional specification, a verification plan with test cases, and a prompt-review checklist to ensure high-fidelity outputs from your target LLM.

How to install

Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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Listed3 months ago

Creator

Roy Yuen

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