Elaborate Spec

SkillDev tools

Guides your agent to interview you about a vague idea and turn it into a clear, detailed specification.

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

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the Elaborate Spec skill

About this skill

Refine a rough idea into a clear, detailed specification through dialogue. Does not produce code. Use when user has a vague idea, wants to think through a feature before planning, or needs to turn "I want X" into a concrete spec.

What this skill tells your AI

The instructions your AI receives, as published by danielvm-git/bigpowers in skills/elaborate-spec/SKILL.md and read by ahel’s review.

Turn a rough idea into a clear specification through focused dialogue. No code is written during this skill — the output is shared understanding and a refined problem statement.

HARD GATE — Do NOT proceed with planning or implementation until the problem space is clearly understood. Success criteria, actors, and scope must be explicit before drafting a plan.

Process

1. Listen first

Let the user describe their idea in their own words. Do not interrupt or redirect. Take notes on:

  • The core problem they're trying to solve
  • Who is affected (actors)
  • What success looks like to them
  • Any constraints they've already identified

2. Ask clarifying questions

Ask one question at a time. Work through these areas:

Problem clarity

  • What is the current behavior (or lack of behavior) that prompted this?
  • Who experiences this problem? How often?
  • What's the cost of not solving it?

Solution boundaries

  • What is explicitly IN scope?
  • What is explicitly OUT of scope?
  • Are there existing solutions (internal or external) this replaces or integrates with?

Success criteria

  • How will you know this is done?
  • What does the happy path look like end-to-end?
  • What are the key failure modes to handle?

Constraints

  • Any performance requirements?
  • Any compatibility constraints (existing APIs, data formats)?
  • Any non-negotiable implementation decisions already made?

2.5. Multiple Interpretations (HARD GATE)

HARD GATE — If the request admits ≥2 valid interpretations, do NOT guess. You must list them and ask the user to choose before proceeding. Proceeding with unresolved ambiguity is a failure of integrity.

Present the options clearly:

"I see two ways to read this:

  1. [Interpretation A] — my recommendation because [reason]
  2. [Interpretation B] Which is closer to what you mean?"

3. Surface hidden assumptions

Once the user has answered the main questions, probe for assumptions:

  • "You mentioned X — does that mean Y is also true?"
  • "What happens when Z fails?"
  • "Is this for internal users, external users, or both?"

4. Synthesize and confirm

Summarize your understanding in 3–5 bullet points aligned with countable-story-format.md:

  • The problem (feeds into §1 Business narrative)
  • The solution and main flow (feeds into §5)
  • The key constraints and alternative flows (feeds into §6)
  • The success criteria (feeds into §17 Gherkin)
  • What's out of scope (feeds into §18)

Ask: "Is this an accurate summary? Anything missing or wrong?"

5. Write specs/planning-context.yaml

After the user confirms the summary in step 4, persist the key decisions:

# specs/planning-context.yaml — written by elaborate-spec; consumed by scope-work and slice-tasks
feature_name: "<from step 1>"
problem_statement: "<one paragraph>"
constraints:
  - "<constraint 1>"
out_of_scope:
  - "<excluded item 1>"
key_decisions:
  - decision: "<what was decided>"
    rationale: "<why>"

If specs/planning-context.yaml already exists, ask: "Planning context from a prior session exists. Update it? [Y/n]". Overwrite on Y; leave unchanged on N.

6. Suggest next skill

Once the spec is clear, recommend the next step:

  • If domain model needs work → model-domain
  • If ready to plan → plan-release (creates epic capsules with epic.yaml + story .md + -tasks.yaml) then plan-work per story
  • If a spike is needed first → spike-prototype
  • If architecture decisions are needed → deepen-architecture or grill-me
  • If the plan depends on a specific library or API → grill-me in docs mode

Signals

GitHub stars
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Forks
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Last commit
Sep 2026
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Item type
skill
Key
elaborate-spec
Source
github.com/danielvm-git/bigpowers