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Elicit Requirements

Community
faizkhairi
elicit-requirements

Structured pre-feature requirements gathering. Run before writing any new feature or API endpoint to clarify scope, acceptance criteria, and technical constraints. Produces: a Requirements Summary (Problem | Scope | Stories | Acceptance Criteria | Out of Scope | Open Questions), presented to the user for confirmation BEFORE saving to a file, so requirements can be edited before they become reference for implementation.

Overview

Publisherfaizkhairi
Repositoryclaude-code-blueprint
Skill nameelicit-requirements
Stars
73
Forks
22
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by faizkhairi on GitHub. Read the source before you install it.

Installation

Install the Elicit Requirements AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/faizkhairi/claude-code-blueprint/tree/main/skills/elicit-requirements
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/faizkhairi/claude-code-blueprint.git /tmp/claude-code-blueprint
mkdir -p .claude/skills
cp -r /tmp/claude-code-blueprint/skills/elicit-requirements .claude/skills/elicit-requirements
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Elicit Requirements in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Elicit Requirements on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Elicit Requirements is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Elicit Requirements: Structured Pre-Feature Clarification

Run this before writing any new feature to avoid scope creep, missed edge cases, and mid-implementation discoveries that force rewrites.

Elicitation Workflow

Work through these sections with the user. Ask grouped questions; do not ask one at a time.


1. Problem Statement

Ask:

  • What problem are we solving, and for whom?
  • What triggers this feature? (user action, external system push, scheduled job, webhook)
  • What is the expected outcome when it works correctly?
  • What is the expected behaviour when it fails?

2. User Roles and Stakeholders

Ask:

  • Which user roles interact with this directly? (admin, developer, end user, external system)
  • Which roles are indirectly affected? (e.g., reports they see change, notifications they receive)
  • For integration features: which external system is involved? (identify from project context or ask)

3. Technical Constraints

For integration or API features, always clarify:

ConstraintQuestions
SystemWhich external system?
DirectionINBOUND (system pushes to us) or OUTBOUND (we push to system)?
TriggerAPI call, webhook, scheduled job, file arrival?
Data formatJSON? XML? CSV? Other?
AuthJWT? API key? mTLS? None (internal only)?
Error handlingRetry? Dead-letter queue? Alert? Silent fail?
IdempotencyMust duplicate calls be safe?

4. Acceptance Criteria

For each piece of functionality, define:

  • What HTTP endpoint (method + path) if applicable
  • What the success response looks like (status code, key fields)
  • What DB rows are created/updated and with which values
  • What external calls are made (APIs, storage, queues)
  • What happens on error (validation fail, external system down, duplicate)

Acceptance criteria must be verifiable without human judgement. If it says "looks good" or "works correctly" it is not an acceptance criterion.

Good: POST /api/v1/orders returns 202 with { "jobId": "<uuid>" } and creates job row with status='PENDING'

Bad: "The endpoint should handle the data correctly"


5. Out of Scope

Explicitly list what is NOT included in this feature to prevent scope creep:

  • Which related endpoints are deferred?
  • Which error scenarios are explicitly not handled yet?
  • Which UI/dashboard elements are not part of this backend feature?

6. Dependencies and Ordering

  • Does this feature depend on another feature being complete first?
  • Does another feature depend on this being complete?
  • What environment is needed to test? (running dev server, specific DB records, external system mock?)

Output

After elicitation, produce a structured summary:

markdown
## Requirements Summary: [Feature Name]

### Problem
[1-2 sentences]

### Scope
- System: [external system if applicable]
- Direction: [inbound/outbound]
- Trigger: [how it starts]

### Stories (ordered by dependency)
1. [Story 1 title]: [one-line description]
2. [Story 2 title]: [one-line description]

### Acceptance Criteria (per story)
**Story 1:**
- ...

### Out of Scope
- ...

### Open Questions
- ...

Step 7: Confirmation Before Saving

After drafting the Requirements Summary, present it to the user in readable markdown and ask:

"Does this requirements summary look complete and accurate? Should I save it?"

Do NOT save until the user confirms (yes / save / proceed / looks good). If the user wants revisions, loop back to the relevant section, update the draft, and re-present.

Only after confirmation: save the requirements to a structured markdown file the user can reference during implementation.

Frequently asked questions

What does the Elicit Requirements AI skill do?

Structured pre-feature requirements gathering. Run before writing any new feature or API endpoint to clarify scope, acceptance criteria, and technical constraints. Produces: a Requirements Summary (Problem | Scope | Stories | Acceptance Criteria | Out of Scope | Open Questions), presented to the user for confirmation BEFORE saving to a file, so requirements can be edited before they become reference for implementation.

Why use Elicit Requirements on TypingMind?

Because you install it once and use it with any model. Elicit Requirements is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Elicit Requirements in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/faizkhairi/claude-code-blueprint/tree/main/skills/elicit-requirements. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Elicit Requirements?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Elicit Requirements?

As many as you like. As long as a model supports skills, you can use Elicit Requirements with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Elicit Requirements AI skill free?

Yes. It is published on GitHub by faizkhairi under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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