write-a-prd

Overview of write-a-prd skill

write-a-prd is a focused skill for turning a vague feature idea into a structured PRD through three things generic prompts often skip: repo exploration, aggressive clarification, and module-level design thinking. It is best for engineers, tech leads, and AI-assisted builders who need a Requirements Planning workflow that is grounded in the actual codebase instead of a polished but disconnected spec.

What write-a-prd actually does

The write-a-prd skill guides an agent to:

• collect a detailed problem description,
• inspect the repository to verify assumptions,
• interview the user until key decisions are explicit,
• propose major modules with an emphasis on deep, testable abstractions,
• turn the result into a PRD suitable for a GitHub issue.

Best-fit users and jobs-to-be-done

Use write-a-prd when you need more than “write me a PRD.” It fits teams that want to:

• scope a new feature against an existing codebase,
• uncover hidden decisions before implementation starts,
• convert product intent into implementation-ready requirements,
• create a GitHub-native planning artifact for review.

Why this write-a-prd skill stands out

The main differentiator is not formatting. It is the workflow discipline:

• repo-first validation instead of trusting the initial brief,
• relentless questioning to resolve ambiguity,
• module sketching before the final document,
• explicit attention to testable deep modules.

That makes it more useful for Requirements Planning than a one-shot PRD prompt.

What to know before installing or adopting

This skill is lightweight: the repository evidence shows only a single SKILL.md file and no helper scripts, templates folder, or support resources. That is good for fast adoption, but it also means output quality depends heavily on the user’s inputs and the agent’s willingness to inspect the repo carefully. If you want rigid templates, automations, or issue-posting scripts, this skill does not provide them by itself.

How to Use write-a-prd skill

write-a-prd install context

The upstream skill itself is just the instruction file at write-a-prd/SKILL.md. There is no skill-specific installer documented inside that file. If you are using a Skills-compatible environment, install or enable the containing repository in the way your agent platform expects, then make sure the write-a-prd slug is available.

If you are evaluating before install, the key file to read is:

• SKILL.md

There are no additional README.md, metadata.json, rules/, or resources/ files for this skill.

Read this file first

Start with SKILL.md and read it end-to-end before first use. Because the repo contains only that file for this skill, all important behavior lives there:

• when the skill should trigger,
• the required interview flow,
• the repo exploration step,
• the module-design expectation,
• the final PRD template.

What input write-a-prd needs

The write-a-prd skill performs best when you provide:

• the problem to solve,
• who experiences it,
• current workaround or pain,
• constraints like deadlines, compatibility, or compliance,
• any early solution ideas,
• the repository or code area to inspect,
• what level of implementation detail you want in the PRD.

Weak input: “Add notifications.”

Strong input: “We need in-app notifications for failed background jobs because users currently miss email alerts. The app is multi-tenant, jobs already emit failure events, and we need an MVP this sprint without mobile push support.”

How to turn a rough idea into a good write-a-prd prompt

A strong write-a-prd usage prompt usually combines business context, codebase scope, and decision constraints in one message. Include:

1. the outcome,
2. the affected users,
3. the relevant repo paths,
4. known constraints,
5. open questions you want the skill to resolve.

Example structure:

• “Help me use write-a-prd for Requirements Planning.”
• “The problem is…”
• “Please inspect these areas of the repo…”
• “Assume these constraints…”
• “Challenge weak assumptions and produce a GitHub-issue-ready PRD.”

Recommended workflow in practice

A practical write-a-prd workflow looks like this:

1. Give the long problem description.
2. Let the agent inspect the codebase before drafting.
3. Answer follow-up questions fully instead of rushing to the template.
4. Review the proposed modules and test boundaries.
5. Only then ask for the final PRD.
6. Post or adapt the output as a GitHub issue.

This sequence matters. If you skip the repo review or the interview stage, the result becomes much closer to a generic PRD prompt.

How the interview phase changes output quality

The strongest part of write-a-prd is its instruction to interview the user “relentlessly.” In practice, that means the agent should pressure-test:

• edge cases,
• user roles,
• operational constraints,
• migration concerns,
• success criteria,
• dependencies between design decisions.

If your agent is not asking enough follow-up questions, the skill is being underused.

Why repo exploration matters for Requirements Planning

For Requirements Planning, the skill’s repo-exploration step is what turns speculation into grounded planning. Ask the agent to verify:

• whether similar functionality already exists,
• which modules are likely affected,
• naming and architectural conventions,
• whether the proposed feature conflicts with current abstractions.

This reduces the classic PRD problem where the document sounds coherent but ignores code reality.

How to use the module sketching step well

The write-a-prd skill explicitly asks for major modules and encourages deep modules that are easy to test and hard to misuse. That means you should ask the agent to identify:

• what should be encapsulated,
• what interface each module exposes,
• where change is likely,
• what deserves isolated tests.

This is especially useful when the PRD is meant to guide implementation, not just stakeholder alignment.

What the final PRD should contain

Based on the upstream template, expect the final PRD to at least cover:

• ## Problem Statement
• ## Solution

The full template in SKILL.md continues beyond the excerpted repository evidence, so review the file directly before standardizing your internal format. If your team requires sections like rollout, analytics, or non-goals, ask the agent to extend the template explicitly.

A strong write-a-prd usage prompt example

Here is a practical prompt shape you can adapt:

“Use the write-a-prd skill to help me plan a feature for this repository. The problem is that admins cannot bulk reassign tickets during org restructures, so teams are doing manual updates. Please inspect the ticketing, permissions, and audit-log code paths first. Constraints: preserve existing RBAC behavior, record all bulk changes, and avoid long-running synchronous requests. Interview me until the scope is clear, propose the main modules, identify which modules should have tests, then draft a GitHub-issue-ready PRD.”

write-a-prd skill FAQ

Is write-a-prd better than a normal PRD prompt?

Usually yes, if your project already has a codebase and implementation constraints. A normal prompt can format a nice document, but write-a-prd is stronger when you need the PRD to reflect repo reality, unresolved tradeoffs, and module boundaries.

Is write-a-prd suitable for beginners?

Yes, with one caveat: beginners must answer follow-up questions patiently. The skill can improve thinking structure, but it does not replace product judgment. If you do not know the codebase, be explicit about that so the agent spends more effort on repo exploration and clarification.

When is write-a-prd a poor fit?

Skip write-a-prd when:

• you only need a one-paragraph concept note,
• there is no repo to inspect,
• the task is a tiny bug fix,
• the decision is already made and you just need prose cleanup,
• your team needs a fixed enterprise PRD schema the skill does not provide.

Does the write-a-prd skill create implementation plans too?

Indirectly. It is primarily for PRD creation, but the module-design step gives you a lightweight architecture bridge into implementation. If you need task breakdowns, milestones, or ticket decomposition, you may need a second planning pass after the PRD.

Does it submit the GitHub issue automatically?

The skill says the PRD should be submitted as a GitHub issue, but the repository evidence does not show automation scripts or issue-posting helpers. Treat the output as issue-ready content, not guaranteed issue automation.

How much repo access should I give the agent?

Enough to inspect the relevant feature area and adjacent modules. Too little access weakens the skill’s main advantage. If access is restricted, provide file paths, architecture notes, and representative code snippets so the write-a-prd skill can still reason from something concrete.

How to Improve write-a-prd skill

Give sharper problem statements, not solution slogans

The most common failure mode is starting with a solution label instead of a user problem. Better inputs describe:

• who is blocked,
• what they are trying to do,
• what fails today,
• why it matters now.

That gives write-a-prd a better base for Requirements Planning than “add X feature.”

Force explicit constraints early

Good PRDs get stronger when constraints are named before the draft. Tell the skill about:

• performance limits,
• backward compatibility,
• security rules,
• rollout deadlines,
• analytics requirements,
• testing expectations.

Without these, the skill may produce a plausible but impractical solution.

Ask the agent to show unresolved decisions

If the first draft feels too certain, ask write-a-prd to separate:

• confirmed decisions,
• assumptions,
• open questions,
• deferred choices.

This is one of the fastest ways to make the output more useful for team review.

Improve the repo exploration step

Do not accept “I reviewed the codebase” at face value. Ask for:

• the files or modules inspected,
• current behavior discovered,
• constraints inferred from existing architecture,
• any mismatch between your initial request and repo reality.

This makes the write-a-prd guide more trustworthy.

Strengthen the module design output

The module step is easy to under-specify. Ask for each proposed module to include:

• responsibility,
• interface shape,
• dependencies,
• why it should be deep rather than shallow,
• whether it should be tested in isolation.

That turns the PRD from product prose into something implementation-relevant.

Iterate after the first PRD draft

The first draft should rarely be the final one. A good refinement loop is:

1. review for missing constraints,
2. mark vague sections,
3. challenge overbuilt solutions,
4. ask for non-goals and success criteria,
5. regenerate only the weak sections.

Targeted rewrites usually outperform “rewrite the whole PRD.”

Add your team’s required sections explicitly

Because the skill is lightweight, do not assume it includes your house style. If your team expects sections like:

• non-goals,
• rollout plan,
• metrics,
• risks,
• migration,
• support impact,

say so in the prompt. write-a-prd is flexible, but it will not invent every governance section unless asked.

Watch for these common failure modes

Common output issues with write-a-prd include:

• jumping to implementation before clarifying the problem,
• insufficient repo grounding,
• shallow module boundaries,
• missing test expectations,
• PRDs that describe features but not success conditions.

Most of these are fixed by better inputs and stricter follow-up review, not by abandoning the skill.