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Evanflow Prd

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evanklem
evanflow-prd

Synthesize a PRD (Product Requirements Document) for a big new feature. Synthesis (not interview) — uses existing project context and explicit ADRs. Asks before gh issue create. Use when scoping a substantial new feature in PRD shape (e.g., before a sprint).

Overview

Publisherevanklem
Repositoryevanflow
Skill nameevanflow-prd
Stars
418
Forks
18
Bundled files
Instructions only
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 evanklem on GitHub. Read the source before you install it.

Installation

Install the Evanflow 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/evanklem/evanflow/tree/main/skills/evanflow-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/evanklem/evanflow.git /tmp/evanflow
mkdir -p .claude/skills
cp -r /tmp/evanflow/skills/evanflow-prd .claude/skills/evanflow-prd
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Evanflow 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 Evanflow 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 Evanflow 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.

EvanFlow: PRD

Vocabulary

See evanflow meta-skill.

When to Use

  • Substantial new feature requiring stakeholder alignment
  • Pre-sprint scoping
  • A spec exists in conversation but needs structured form for the team

SKIP when: the work is small enough for evanflow-brainstorming → evanflow-writing-plans directly.

The Flow

1. Read Context (don't interview)

The skill name is "to-prd" not "interview-to-prd" for a reason. Synthesize from what's already known:

  • CLAUDE.md for project conventions
  • CONTEXT.md for domain language
  • docs/adr/ for prior architectural decisions
  • Recent commits and docs/stakeholder/*.md for in-flight initiatives
  • The conversation up to this point

Only ask the user for things you genuinely cannot derive.

2. Identify Major Modules

Sketch the modules to build/modify, emphasizing deep modules (small interface, complex internals). Apply the deletion test to each — does this module earn its existence?

3. Validate Architecture

Confirm with the user:

  • The module list (correct, exhaustive, no gaps)
  • Which components require test coverage (you can't test everything)
  • Which existing patterns to follow vs. diverge from

4. Write the PRD

Default location: docs/specs/YYYY-MM-DD-<feature>.md. Use the user's preferred path if they have one.

Structure:

markdown
# [Feature Name] PRD

## Problem

One paragraph: what's broken or missing in the current product, and who feels the pain.

## Solution

One paragraph: the shape of the answer, named in domain language.

## User stories

- As a <role>, I can <action> so that <outcome>.
- (List 5-15)

## Architecture

Module list with one-line responsibility per module. Reference existing files where relevant. No code paths.

## Testing strategy

What behaviors must be covered. Integration vs. unit. Real services vs. test doubles.

## Scope

In:
- ...

Out:
- ...

## Open questions

Things needing decision before the plan can be written.

5. Optional: Create GitHub Issue

If the user wants the PRD as a GitHub issue, ASK before running gh issue create. Never auto-file.

Hard Rules

  • Synthesize, don't interrogate. Ask only for genuinely unknown things.
  • Domain language from CONTEXT.md. Use canonical terms.
  • External behavior over implementation. Testing strategy describes what to verify, not how.
  • Asks before gh issue create. No auto-file.
  • Never auto-commit. PRD doc gets staged; user confirms before commit.

Hand-offs

  • PRD approved, ready for plan → evanflow-writing-plans. If the PRD's module list shows 3+ independent components sharing a contract, the plan should be structured for evanflow-coder-overseer.
  • New domain terms emerged → evanflow-glossary to update CONTEXT.md
  • PRD reveals architecture concerns → evanflow-improve-architecture first
  • PRD's interface design needs more thought → evanflow-design-interface before plan

Frequently asked questions

What does the Evanflow Prd AI skill do?

Synthesize a PRD (Product Requirements Document) for a big new feature. Synthesis (not interview) — uses existing project context and explicit ADRs. Asks before gh issue create. Use when scoping a substantial new feature in PRD shape (e.g., before a sprint).

Why use Evanflow Prd on TypingMind?

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

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

Which AI models can use Evanflow 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 Evanflow Prd?

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

Is the Evanflow Prd AI skill free?

It is published on GitHub by evanklem. Check the repository for licensing terms. 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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