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Prd And Stories

Community
nahid-sparktales
prd-and-stories

Write a scope someone else can build from without asking you what you meant — problem, users, the flow end to end including its unhappy states, acceptance criteria phrased as observable behaviour, and explicit non-goals. Use when turning a settled problem into a brief, spec, PRD, epic or set of stories, or when repairing a ticket that is too vague to estimate or to check. Not for deciding whether the problem is real (product-discovery), not for ranking work (prioritization), and not for choosing the implementation.

Overview

Publishernahid-sparktales
Repositoryagent-dispatcher
Skill nameprd-and-stories
Stars
58
Forks
5
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

    Published by nahid-sparktales on GitHub. Read the source before you install it.

Installation

Install the Prd And Stories 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/nahid-sparktales/agent-dispatcher/tree/main/skills/product/prd-and-stories
  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/nahid-sparktales/agent-dispatcher.git /tmp/agent-dispatcher
mkdir -p .claude/skills
cp -r /tmp/agent-dispatcher/skills/product/prd-and-stories .claude/skills/prd-and-stories
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Prd And Stories 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 Prd And Stories 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 Prd And Stories 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.

PRD and stories

The test of a scope is not that it reads well. It is that two people building from it independently produce the same behaviour, and a third can tell whether they did.

When this fires

A problem is settled and the work needs a written scope before it is designed or built; a ticket is too vague to estimate, to build, or to check. It does not fire while the problem is still in question — go back to product-discovery and say why.

Procedure

  1. Check the problem is actually settled. One paragraph: who, doing what, blocked how, and what evidence says so — with the grade it came with (observed, reported, assumed). If you are writing that paragraph from imagination, stop and say the scope is resting on an unchecked belief.
  2. State the change in the world. What will be true after this ships that is not true now, expressed as user behaviour or outcome, not as a shipped artifact. "An agent can see the audit trail while closing a refund", not "we add an audit panel".
  3. Inspect the surface you are scoping. Read the current screens, routes, data model and permissions before describing the new ones. A scope that contradicts what exists costs more to discover in review than to prevent here, and existing conventions are usually load-bearing.
  4. Write the primary flow end to end. Entry point (how does anyone arrive), each step and its decision points, the exit and what the user sees when it worked. Number the steps. If a step needs data the system does not have, name that now — it is the most common hidden dependency.
  5. Write the states that are not the happy path. Empty, loading, partial, error, offline or slow, no permission, and the boundary values (zero, one, very many, very long, duplicate, concurrent). Each one gets a stated intended behaviour. Unspecified states are not neutral: somebody will invent them, and reviewers will not know what to check against.
  6. Write acceptance criteria as observable behaviour. One checkable statement per criterion, in the form "given … when … then …" or a plain sentence a tester can execute. Each must name what is done and what can be seen. Forbidden in a criterion: "works correctly", "is intuitive", "is performant" with no number, and any verb about the process rather than the product — created, executed, tested, reviewed, deployed and verified describe what a team did, and none of them is a behaviour a user can observe. If a criterion cannot fail, it is a description, so delete it or sharpen it.
  7. Write the non-goals explicitly. The adjacent things a reasonable reader would assume are included: the admin view, the bulk case, the other platform, the migration of old data, the analytics event. Naming them as out is what stops silent scope growth later.
  8. Cover the cross-cutting requirements that are usually skipped. Who is allowed to do this (permissions, roles, tenancy); what data is stored, shown or logged, and what must not be; keyboard and screen-reader access to the new controls; what operations need to see when it misbehaves. Write the ones that apply and say the rest do not.
  9. Split into stories only along lines that ship. Each story is independently buildable and independently checkable, and carries its own acceptance criteria. Split by user-visible slice — one flow working end to end for one case — not by layer. "Build the API", "build the UI" is a task list wearing a story's clothes: neither half can be checked against a user.
  10. List the open questions with an owner and a blocking flag. A question you invented an answer for is the failure mode this step exists to prevent. Mark which ones must be answered before building and which can be answered while building.
  11. Hand over with the decided and the open kept apart. The scope fixes behaviour and constraints; it does not choose the implementation. Where you have a preference about how, say it is a preference. Leave design and architecture their decisions.

Checklist

  • Problem paragraph present, with the evidence grade it carries
  • Outcome stated as a change in what a user can do
  • Current behaviour was read, not assumed
  • Primary flow numbered from entry point to exit
  • Empty, error, permission-denied and boundary states each have stated behaviour
  • Every acceptance criterion is observable and can fail
  • No criterion uses created / executed / tested / reviewed / deployed / verified as its behaviour
  • Non-goals written, including the obvious adjacent ones
  • Permissions, data, accessibility and operational needs covered or explicitly N/A
  • Stories split by shippable slice, each with its own criteria
  • Open questions listed with owners, blocking ones marked
  • Nothing in the scope dictates implementation without saying it is a preference

Failure handling

  • A required answer does not exist. Write the question, not a plausible answer. A spec's invented detail is indistinguishable from a decided one by the time it reaches a developer.
  • The scope will not fit the time available. That is a prioritization problem, not a writing problem. Name the smallest slice that delivers the outcome, and say what was cut — do not shrink the criteria until everything fits.
  • A criterion depends on a number nobody has. Propose the number, label it a proposal, and name who confirms it. A target presented as agreed when it was guessed is a defect in the spec.
  • Existing behaviour contradicts the new scope. Raise it as a decision — change it, keep it, or scope around it — and do not resolve it silently in the spec's wording.
  • The scope touches deletion, money, messaging users, or anything else irreversible. Specify the confirmation and the recovery path as part of the behaviour, and flag it for explicit sign-off. Writing it down is not approval to build or run it.
  • You are being asked to sign off on the work as well as write the scope. Decline the second half. Whoever wrote the criteria is not the evidence that they pass.

Evidence to report

The written scope itself; the source of the problem paragraph; which files or screens you read to describe current behaviour; the states you specified and any you deliberately left out; the acceptance criteria, each one checkable; the non-goals; and the open questions with owners. A brief with no non-goals and no open questions is usually not complete — it is unexamined.

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 Prd And Stories AI skill do?

Write a scope someone else can build from without asking you what you meant — problem, users, the flow end to end including its unhappy states, acceptance criteria phrased as observable behaviour, and explicit non-goals. Use when turning a settled problem into a brief, spec, PRD, epic or set of stories, or when repairing a ticket that is too vague to estimate or to check. Not for deciding whether the problem is real (product-discovery), not for ranking work (prioritization), and not for choosing the implementation.

Why use Prd And Stories on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nahid-sparktales/agent-dispatcher/tree/main/skills/product/prd-and-stories. 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 Prd And Stories?

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 Prd And Stories?

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

Is the Prd And Stories AI skill free?

Yes. It is published on GitHub by nahid-sparktales 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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