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Hai Prd

Community
hylarucoder
hai-prd

Decides whether a PRD is needed, drafts one from a product problem, repairs an existing PRD, or judges its split/merge boundary. Use for PRDs, product requirements, requirement specs, scope, user-visible behavior, and acceptance criteria(写 PRD、需求文档、PRD 拆分或打磨). Use hai-goal for execution phases, hai-architecture for technical design, entity-model-auditor for field placement, and document-audit skills when the task is consistency diagnosis rather than product shaping.

Overview

Publisherhylarucoder
Repositoryhai-stack
Skill namehai-prd
Stars
284
Forks
15
Bundled files
5
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.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Hai 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.
  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/hylarucoder/hai-stack.git /tmp/hai-stack
mkdir -p .claude/skills
cp -r /tmp/hai-stack/skills/hai-prd .claude/skills/hai-prd
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hai 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 Hai 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 Hai 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.

Hai PRD

For Chinese readers, see SKILL.zh_CN.md. The English SKILL.md is the execution source of truth.

Overview

Handle all PRD-related work: deciding whether a PRD is even needed, choosing PRD granularity, splitting or merging PRDs, drafting a PRD from a product problem, and refining an existing one.

The non-obvious framing: a PRD is not the default artifact. Not every idea, field, API, configuration change, or technical decision earns one. Pick the mode that fits the request and do not wrap work in a PRD when there is no product boundary or acceptance to prove.

Core Principle

A PRD is a product argument with verifiable acceptance — not a feature list. Three rules carry the rest:

  • Acceptance must be provable. One PRD should resolve one clear outcome, one main user journey or product boundary, and acceptance criteria that prove it shipped.
  • Boundary follows the user's mental model, not the tech. Granularity tracks user journeys and independent acceptance — not technical layers, teams, or files.
  • Fix the boundary before the wording. If the PRD boundary is wrong, split, merge, or reframe it before polishing local sentences; edit an existing PRD as a system where goal, scope, behavior, acceptance, risks, and rollout must agree.

Modes

1. Need PRD

First decide the artifact type — a PRD is one option among several:

SituationBetter artifact
User or business behavior changes and goal, scope, and acceptance need alignmentPRD
Execution goal, phases, and verification are the main needhai-goal
Architecture, module boundaries, or technical tradeoffs are the main needhai-architecture
The main question is whether the idea is worth doing at allhai-idea
The work is a code task, bugfix, or test-first implementationhai-tdd or task note
The work is documentation consistency auditinghai-audit-docs

Ask:

  • Is there a user-, buyer-, operator-, maintainer-, or business-visible behavior change?
  • Does the work need explicit in-scope and out-of-scope boundaries?
  • Does it need acceptance criteria to prove it was done correctly?
  • Are there product-level options, risks, constraints, or rollout concerns to record?
  • Would the team disagree on goal, scope, or acceptance without a PRD?

If most answers are no, do not force a PRD. When auditing a set of PRDs, also check for duplicate boundaries, circular dependencies, or broken user journeys across them.

2. Design PRD

Turn a feature idea or product problem into PRD-level requirements:

  1. Gather context. Target user, product surface, current behavior, desired outcome, constraints, assumptions; plus existing PRDs, docs, screenshots, user flows, issues, data, or adjacent specs.
  2. Frame the requirement. Write the problem in product language; define the target outcome and non-goals; identify the user journey or workflow boundary; separate facts, assumptions, and open questions.
  3. Shape scope. Decide what belongs in this PRD versus another PRD, design doc, goal, or task. Do not bundle unrelated cleanup, platform work, or refactors unless they directly affect product behavior or acceptance.
  4. Define behavior and acceptance. Describe expected behavior by scenario; add observable acceptance criteria; include edge cases, failure states, permissions, empty states, data dependencies, and rollout only when relevant.

3. Craft PRD

Refine an existing PRD as a whole product argument:

  1. Read the full document first. Identify title, target user, goal, journey, scope, non-goals, acceptance, risks, and open questions; mark contradictions, duplication, stale sections, local patches, and unreasonable content.
  2. Diagnose document drift using this taxonomy:
    • Goal drift: sections optimize for different outcomes.
    • Scope drift: requirements pull in unrelated work.
    • Conflict drift: behavior, state, permissions, data, or rollout disagree across sections.
    • Acceptance drift: acceptance criteria cannot prove the target outcome.
    • Solution drift: implementation choices replace product requirements.
    • Local-edit drift: one section improves while the whole PRD becomes worse.
  3. Reframe before rewriting. State the corrected target outcome and the PRD boundary; decide whether to preserve, reorganize, split, merge, or rewrite.
  4. Craft the document. Edit directly when the user provides a file; preserve useful content but move it to the right section; remove unsupported, duplicated, obsolete, or out-of-scope content; explain why removal beats rewriting or moving when content is deleted.

4. Scope PRD

Judge PRD granularity by user mental model and independent acceptance, not technical modules or teams. Run the six tests — this is the decision core:

TestQuestionSignal
Press ReleaseCan one sentence express one clear user value?Multiple unrelated values lean split
Independent ValueDoes this PRD deliver value on its own?Independent value can split; no value leans merge
Independent AcceptanceCan it be accepted independently?Independent acceptance can split
Domain LanguageDoes it share the same core entity, terminology, and lifecycle?Same entity leans merge; different contexts lean split
User JourneyDoes splitting break the user journey?Broken journey means do not split
Time AppetiteIs the scope controlled?Too large should split or cut; too small should merge

When the tests point toward split or merge, read references/scope-tiers.md to pick a concrete cut: the preferred split dimensions, the splits to avoid (technical layer / CRUD / team ownership, because no such fragment is independently acceptable), the three-tier classification (entity lifecycle / aggregate view / platform extension), and the new-feature decision flow.

Workflow

  1. Pick the mode from the request: necessity check → Need PRD; draft from a problem → Design PRD; refine an existing doc → Craft PRD; split/merge/granularity → Scope PRD. A request may span modes (e.g. necessity then scope).
  2. Run that mode's procedure above. Apply the Core Principle throughout — fix the boundary before the wording.
  3. For split/merge questions, run the six tests, then consult references/scope-tiers.md for the concrete cut and classification.
  4. Produce the output for the active mode (see below). When a worked run helps, read references/worked-example.md for an end-to-end split decision and an end-to-end craft/diagnosis.

Output

Read references/output-template.md and fill only the active mode's sections. Do not mechanically emit every mode or duplicate the template here. A necessity check can be brief; a draft or repair must carry enough product behavior and acceptance detail to stand alone.

Use a different skill when

Routing away from a PRD is the Need-PRD decision itself — see the table in Mode 1. In short: settle execution phases/todos in hai-goal, module boundaries and tradeoffs in hai-architecture, whether the idea is worth doing in hai-idea, a code/bugfix/test-first task in hai-tdd, what fields an entity should have and where they live in entity-model-auditor, documentation consistency in the doc-audit skills, and an anchor-first rewrite of a drifted non-PRD document in hai-rewrite-doc. Return to PRD work only when a product boundary and provable acceptance actually need to exist.

What this skill is NOT

  • Not project management — do not assign owners or dates unless asked.
  • Not a wrapper that turns every idea into a PRD — if there is no product boundary or acceptance need, recommend the right artifact from the Need-PRD table instead of forcing a PRD.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Hai Prd AI skill do?

Decides whether a PRD is needed, drafts one from a product problem, repairs an existing PRD, or judges its split/merge boundary. Use for PRDs, product requirements, requirement specs, scope, user-visible behavior, and acceptance criteria(写 PRD、需求文档、PRD 拆分或打磨). Use hai-goal for execution phases, hai-architecture for technical design, entity-model-auditor for field placement, and document-audit skills when the task is consistency diagnosis rather than product shaping.

Why use Hai Prd on TypingMind?

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

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

Which AI models can use Hai 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 Hai Prd?

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

Is the Hai Prd AI skill free?

It is published on GitHub by hylarucoder. 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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