to-prd

to-prd is a skill for Claude Code, Codex from a9a4k/vscode-deck. It costs 36 tokens per session (652 once invoked), scanned A, a copy of to-spec, MIT.

A workflow that turns the current conversation and codebase understanding into a product requirements document, or PRD—a written plan describing what should be built—and publishes it to an issue tracker.

In plain words
What is it for?
Use it to create a PRD from existing context, outline the modules involved, account for project decisions, and publish the result with a ready-for-agent label.
Why use it?
It captures the known problem, modules, project terminology, architecture decisions, and implementation expectations in one trackable document.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/a9a4k/vscode-deck/to-prd
Any agent
npx skills add a9a4k/vscode-deck --skill to-prd
Clone the repo
git clone --depth 1 https://github.com/a9a4k/vscode-deck

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for to-prd

README.md
[![agentmods](https://agentmods.dev/badge/skills/a9a4k/vscode-deck/to-prd.svg)](https://agentmods.dev/skills/a9a4k/vscode-deck/to-prd)
Your own site
<a href="https://agentmods.dev/skills/a9a4k/vscode-deck/to-prd"><img src="https://agentmods.dev/badge/skills/a9a4k/vscode-deck/to-prd.svg" alt="Measured on agentmods" height="20"></a>
Per session 36 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 652 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 81% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00036 $0.00652
Opus 5 $0.00018 $0.00326
Sonnet 5 $0.00007 $0.00130
Haiku 4.5 $0.00004 $0.00065

Measured 5d ago against content hash 25b7cc575152, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

to-prd scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

81% identical to to-spec — 29 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.agents/skills/to-prd/SKILL.md · 79 lines

How it starts

The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.

This skill takes the current conversation context and codebase understanding and produces a PRD. Do NOT interview the user — just synthesize what you already know.

The issue tracker and triage label vocabulary should have been provided to you — run /setup-matt-pocock-skills if not.

Process

  1. Explore the repo to understand the current state of the codebase, if you haven't already. Use the project's domain glossary vocabulary throughout the PRD, and respect any ADRs in the area you're touching.

  2. Sketch out the major modules you will need to build or modify to complete the implementation. Actively look for opportunities to extract deep modules that can be tested in isolation.

A deep module (as opposed to a shallow module) is one which encapsulates a lot of functionality in a simple, testable interface which rarely changes.

Check with the user that these modules match their expectations. Check with the user which modules they want tests written for.

  1. Write the PRD using the template below, then publish it to the project issue tracker. Apply the ready-for-agent triage label - no need for additional triage.

Problem Statement

The problem that the user is facing, from the user's perspective.

Solution

The solution to the problem, from the user's perspective.

User Stories

A LONG, numbered list of user stories. Each user story should be in the format of:

  1. As an , I want a , so that

This list of user stories should be extremely extensive and cover all aspects of the feature.

Implementation Decisions

A list of implementation decisions that were made. This can include:

  • The modules that will be built/modified
  • The interfaces of those modules that will be modified
  • Technical clarifications from the developer
  • Architectural decisions
  • Schema changes
  • API contracts
  • Specific interactions

Read the full file on GitHub · 79 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 5d ago First seen · 79 lines · 36 tokens per session scan A 25b7cc575152

Subscribe to this mod's changes

to-prd is a skill published in the GitHub repository a9a4k/vscode-deck (10 stars, last pushed yesterday), licensed MIT. It adds 36 tokens to every session and 652 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 81% identical to to-spec, differing in 29 lines, and is treated as a copy.

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