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slidespeak-onbrand: Skill for Claude Code

.agents/skills/to-prd/SKILL.md

to-prd is a skill for Claude Code, Codex from SlideSpeak/slidespeak-onbrand. It costs 35 tokens per session (716 once invoked), scanned A, a copy of to-spec, MIT.

A way to turn the current conversation and understanding of a codebase into a local product requirements document, or PRD. A PRD records what should be built and the main work needed to build it.

In plain words
What is it for?
It helps document feature requirements, outline implementation areas, identify testable modules, and save the result as a Markdown file in the project.
Why use it?
It creates a written reference for the requested work without requiring a separate interview. It also captures relevant codebase terminology, design decisions, and possible module changes.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

This is SlideSpeak/slidespeak-onbrand's own configuration. It tells Claude Code and Codex how to work on slidespeak-onbrand itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything slidespeak-onbrand configures →

not rated 7repo 1mo ago A scan 35 tokens copy · 70% MIT
View source ↗ SlideSpeak/slidespeak-onbrand slidespeak.co
Reuse

Borrowing it

Nothing to install: this file belongs to SlideSpeak/slidespeak-onbrand. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/SlideSpeak/slidespeak-onbrand/develop/.agents/skills/to-prd/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/SlideSpeak/slidespeak-onbrand

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/slidespeak/slidespeak-onbrand/to-prd/github.svg)](https://agentmods.dev/skills/slidespeak/slidespeak-onbrand/to-prd)
Your own site
<a href="https://agentmods.dev/skills/slidespeak/slidespeak-onbrand/to-prd"><img src="https://agentmods.dev/badge/skills/slidespeak/slidespeak-onbrand/to-prd/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for to-prd

Your own site · 80×15
<a href="https://agentmods.dev/skills/slidespeak/slidespeak-onbrand/to-prd"><img src="https://agentmods.dev/badge/skills/slidespeak/slidespeak-onbrand/to-prd.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 35 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 716 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 70% 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 5.1 $0.00035 $0.00716
Opus 5.5 $0.00014 $0.00286
Sonnet 5.5 $0.00007 $0.00143
Haiku 4.5 $0.00003 $0.00072

Measured 2mo ago against content hash 4e90a0217a52, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, 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 2mo 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

70% identical to to-spec — 49 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 · 97 lines

How it starts

The opening of the file, as written. The whole thing — 97 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 unless a critical ambiguity blocks writing a useful PRD.

The PRD is written locally as a Markdown file at the repository root. Do not publish to an issue tracker from this skill.

Output file

  • Default path: PRD.md
  • If PRD.md already exists, write to PRD-<short-topic-slug>.md instead of overwriting it.
  • If the user explicitly provides a filename, use that path.

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 save it to the chosen local Markdown file. After writing, report the file path only.

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 extensive and cover all aspects of the feature.

Implementation Decisions

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

Read the full file on GitHub · 97 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. 2mo ago First seen · 97 lines · 35 tokens per session scan A 4e90a0217a52

Subscribe to this mod's changes

to-prd is a skill published in the GitHub repository SlideSpeak/slidespeak-onbrand (7 stars, last pushed 1mo ago), licensed MIT. It adds 35 tokens to every session and 716 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 70% identical to to-spec, differing in 49 lines, and is treated as a copy.

PlanningWriting and docs
Related

to-prd compared with skills from other repositories

to-prd next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
to-prdSlideSpeak/slidespeak-onbrandSkill71mo agoMITA35Claude Code, Codex
imagegenopenai/codexSkill134ktodayApache-2.0A113Codex
playwright-climicrosoft/playwrightSkill99ktodayApache-2.0A19Claude Code
local-ai-agentsmicrosoft/ai-agents-for-beginnersSkill79ktodayMITA200Claude Code, Codex
systematic-debuggingobra/superpowersSkill314k3d agoMITA21Claude Code
next-cache-components-adoptionvercel/next.jsSkill143kyesterdayMITA95Claude Code
next-partial-prefetching-adoptionvercel/next.jsSkill143kyesterdayMITA103Claude Code