Skill

Convert requirements into structured PRDs for agents

Turn the current conversation directly into a published PRD - no interview, just synthesis of what's already been discussed.

Works with githublinear

78
Spark score
out of 100
Updated last month
Source checked Aug 21, 2026
Version 15.16.0

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Why it matters

Transform vague feature requests into detailed, structured Product Requirements Documents that align development teams and AI agents on what to build, which modules to touch, and how changes fit into the existing codebase architecture.

Outcomes

What it gets done

01

Quiz stakeholders about requirements and affected modules before writing specs

02

Document architectural decisions and shared language in CONTEXT.md files

03

Generate PRDs that specify implementation scope and design constraints

04

Integrate with GitHub or Linear to pull context from existing issues and tickets

Install

Add it to your toolbox

Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/ag-to-prd | bash

After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.

Reports

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Overview

To Prd

Synthesizes the current conversation and codebase understanding into a structured PRD - problem, user stories, implementation and testing decisions - and publishes it to the issue tracker. Use when a feature has already been discussed in conversation and needs to become a published, agent-ready PRD without a separate interview.

What it does

To Prd takes the current conversation and codebase understanding and produces a PRD without interviewing the user - it synthesizes what's already been discussed rather than asking new questions. It requires the project's issue tracker and triage-label vocabulary to already be configured (via /setup-matt-pocock-skills if not), and publishes the finished PRD there with a ready-for-agent triage label applied, needing no further triage step.

When to use - and when NOT to

Use it when the request matches turning the current conversation into a PRD and publishing it to the project issue tracker. Before writing, it explores the repo if that hasn't already happened, uses the project's own domain glossary vocabulary throughout the document, and respects any ADRs in the area being touched rather than re-litigating settled decisions.

Inputs and outputs

Before writing, it sketches the seams at which the feature will be tested, preferring existing seams to new ones and the highest seam possible - the fewer seams across the codebase, the better, with one as the ideal - checking with the user that the chosen seams match their expectations. The PRD itself follows a fixed template: a Problem Statement and Solution written from the user's perspective, an extensive numbered list of User Stories in the form "As an [actor], I want a [feature], so that [benefit]" covering all aspects of the feature, Implementation Decisions (modules, interfaces, technical clarifications, architectural decisions, schema changes, API contracts) that deliberately excludes file paths or code snippets since they go stale quickly - except a prototype-derived snippet that encodes a decision more precisely than prose can (a state machine, reducer, schema, or type shape), trimmed to just the decision-rich parts rather than a working demo - Testing Decisions (what makes a good test, focused on external behavior not implementation details, plus prior art from similar tests already in the codebase), an Out of Scope section, and Further Notes.

1. As a mobile bank customer, I want to see balance on my accounts, so that I can make better informed decisions about my spending

Integrations

Publishes directly to the project's configured issue tracker with the ready-for-agent triage label, and cross-references the project's domain glossary and existing ADRs rather than introducing new vocabulary or re-deciding settled architecture questions.

Who it's for

Teams that have already talked through a feature in conversation and want that discussion synthesized straight into a structured, agent-ready PRD - user stories, implementation and testing decisions, and scope boundaries - without a separate requirements-gathering interview.

FAQ

Common questions

Discussion

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