idea-to-spec

SkillAI & models

Converts vague ideas into concrete, testable specifications with acceptance criteria. No implementation begins without a spec.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the idea-to-spec skill

What this skill tells your AI

The instructions your AI receives, as published by developersglobal/ai-agent-skills in skills/idea-to-spec/SKILL.md and read by ahel’s review.

Overview

Vague ideas produce vague implementations. This skill transforms any idea — no matter how fuzzy — into a concrete specification with clear scope, acceptance criteria, and non-goals.

When to Use

  • At the start of any new feature
  • When a request is ambiguous
  • Before creating tasks or writing any code

Process

Step 1: Capture the Core Problem

  1. Write: "Users currently can't [do X], which causes [pain Y]."
  2. Identify: who has this problem? How often? What's the impact?
  3. Distinguish problem from solution — don't spec a solution until the problem is understood.

Verify: You can state the problem without mentioning any implementation.

Step 2: Define Success

  1. Write 3–7 acceptance criteria in this format:
    Given [context]
    When [action]
    Then [outcome]
    
  2. Each criterion must be binary — either it passes or it doesn't.
  3. Include negative cases: "Given X, the system must NOT do Y."

Verify: A QA engineer can test each criterion without asking for clarification.

Step 3: Define Scope

  1. In scope: List what is explicitly included.
  2. Out of scope: List what is explicitly excluded — as important as what's included.
  3. Open questions: List any decisions that still need resolution before implementation.

Verify: The out-of-scope list has at least 2 items.

Step 4: Define Non-Functional Requirements

  1. Performance: response time, throughput, scale targets.
  2. Security: auth requirements, data sensitivity.
  3. Reliability: uptime SLA, acceptable error rate.

Verification

  • Problem statement written without mentioning implementation
  • Acceptance criteria in Given/When/Then format
  • Each criterion is binary (pass/fail)
  • Explicit out-of-scope list
  • Open questions listed

References

Signals

GitHub stars
66
Forks
9
Last commit
May 2026
Advanced
Catalog kind
skill
Gateway key
idea-to-spec
Source
github.com/developersglobal/ai-agent-skills