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Doncheli Prd

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doncheli
doncheli-prd

Generate professional Product Requirement Documents (PRD) from multiple sources — Figma designs, briefs, user research, existing code. Includes risk analysis, RICE prioritization, Gherkin stories and launch plan. Activate when user mentions "PRD", "product requirements", "requirement document", "product spec", "figma to PRD", "generate PRD".

Overview

Publisherdoncheli
Repositorydon-cheli-sdd
Skill namedoncheli-prd
Stars
59
Forks
12
Bundled files
Instructions only
LicenseApache-2.0
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 doncheli on GitHub. Read the source before you install it.

Installation

Install the Doncheli Prd 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/doncheli/don-cheli-sdd/tree/main/.agent/skills/doncheli-prd
  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/doncheli/don-cheli-sdd.git /tmp/don-cheli-sdd
mkdir -p .claude/skills
cp -r /tmp/don-cheli-sdd/.agent/skills/doncheli-prd .claude/skills/doncheli-prd
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Doncheli Prd 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 Doncheli Prd 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 Doncheli Prd 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.

Don Cheli: PRD Generator

Instructions

  1. Discover sources — Identify all available inputs:

    • Figma links: analyze screens, flows, components, missing states
    • Brief documents: extract objectives, audience, problems
    • User research: identify personas, JTBD, pain points
    • Existing code: detect technical constraints
    • Conversation context: extract requirements mentioned by the user
  2. Analyze Figma (if provided):

    • Count screens/frames and map navigation flow
    • Extract texts, labels, form fields, interactions
    • Detect missing UI states: loading, empty, error, success, offline
    • Identify gaps: flows not designed, edge cases missing
    • Convert each screen → user stories → acceptance criteria
  3. Risk analysis — For each feature, evaluate 7 risk categories:

    • Technical (complexity, integrations, tech debt)
    • Product (market fit, adoption, competition)
    • UX (usability, accessibility, learning curve)
    • Business (revenue, cost, time-to-market)
    • Legal (GDPR, compliance, ToS)
    • Security (OWASP, sensitive data, auth)
    • Operational (support, scalability, monitoring)
    • Assign probability (Low/Medium/High) and impact (Low/Medium/High/Critical)
    • Propose mitigation for each risk
  4. Prioritize features using MoSCoW + RICE:

    • MoSCoW: Must / Should / Could / Won't
    • RICE: (Reach × Impact × Confidence) / Effort
    • Rank features by RICE score
  5. Generate PRD with 13 sections:

    1. Executive Summary
    2. Problem (context, pain points, evidence)
    3. Objectives & Success Metrics (KPIs, North Star)
    4. Target Audience (personas, JTBD, user journey)
    5. Proposed Solution (overview, main flow, features by priority)
    6. Detailed Requirements (functional with Gherkin, non-functional, integrations, data model)
    7. Design & UX (Figma analysis, UI states, responsive, accessibility)
    8. Risk Analysis (matrix, mitigations, dependencies)
    9. Scope (in scope, out of scope, future iterations)
    10. Timeline & Milestones
    11. Competitive Analysis
    12. Launch Plan (rollout, monitoring, rollback)
    13. Appendices (glossary, references, change history)
  6. Validate PRD quality:

    • Every requirement must be verifiable/testable
    • Success metrics must be defined with baseline and target
    • Every risk must have a mitigation
    • Scope must be realistic for the timeline
    • Anti-scope (out of scope) must be explicit

Output Format

markdown
# PRD: [Product/Feature Name]

## Metadata
| Field | Value |
|-------|-------|
| Version | 1.0 |
| Author | [name] |
| Status | Draft / In Review / Approved |
| Date | [date] |

## 1. Executive Summary
...
(continue with all 13 sections)

Save output to:

  • .dc/prd/prd-v1.0.md — Full PRD
  • .dc/prd/prd-risks.md — Expanded risk matrix
  • .dc/prd/prd-figma-analysis.md — Figma analysis (if applicable)

Integration with SDD Pipeline

After generating the PRD, suggest:

/dc:specify    → Convert user stories into Gherkin specs
/dc:tech-plan  → Generate blueprint from the PRD
/dc:breakdown  → Create TDD tasks from the stories

Templates

Select based on product type:

  • saas — B2B platforms, dashboards, multi-tenant
  • mobile — Native iOS/Android, PWA
  • ecommerce — Online stores, marketplaces
  • api — Public APIs, SDKs, developer platforms
  • internal — Internal team tools
  • landing — Landing pages, conversion funnels

Quality Gate

  • Never generate a PRD without at least 1 verifiable success metric
  • Never omit the risk section — if no risks are visible, dig deeper
  • Never leave scope ambiguous — mark unclear items as [NEEDS CLARIFICATION]
  • Always include explicit anti-scope (what will NOT be built)
  • Always generate user stories in Gherkin format for SDD integration
  • Always version the PRD (v1.0, v1.1) with change history

Do not use this skill when

  • The task is a simple bug fix or hotfix — use /dc:quick instead
  • The user only needs technical specs — use /dc:specify directly
  • The requirement is already well-defined in Gherkin — skip PRD, go to plan

Frequently asked questions

What does the Doncheli Prd AI skill do?

Generate professional Product Requirement Documents (PRD) from multiple sources — Figma designs, briefs, user research, existing code. Includes risk analysis, RICE prioritization, Gherkin stories and launch plan. Activate when user mentions "PRD", "product requirements", "requirement document", "product spec", "figma to PRD", "generate PRD".

Why use Doncheli Prd on TypingMind?

Because you install it once and use it with any model. Doncheli Prd 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 Doncheli Prd in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/doncheli/don-cheli-sdd/tree/main/.agent/skills/doncheli-prd. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Doncheli Prd?

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 Doncheli Prd?

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

Is the Doncheli Prd AI skill free?

Yes. It is published on GitHub by doncheli under the Apache-2.0 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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