to-prd

A workflow for turning the current conversation into a product requirements document and publishing it to an issue tracker. A product requirements document explains what should be built, and an issue tracker records work for a development team.

In plain words
What is it for?
Use it to create a concise feature specification, record testing decisions and scope, and publish the result as a ready-for-development issue.
Why use it?
It captures decisions already made in the conversation in a form developers can use, without starting another requirements interview.

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/voidtechnology/voidtech-claude-plugins/to-prd
Any agent
npx skills add VoidTechnology/voidtech-claude-plugins --skill to-prd
Clone the repo
git clone --depth 1 https://github.com/VoidTechnology/voidtech-claude-plugins

Made for: Claude Code, Codex.

Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,103 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found 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 $0.00037 $0.01103
Opus 5 $0.00018 $0.00551
Sonnet 5 $0.00007 $0.00221
Haiku 4.5 $0.00004 $0.00110

Measured yesterday against content hash 9d541f16202d, 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 yesterday.

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.

plugins/voidtech-engineering/skills/to-prd/SKILL.md · 87 lines

What it actually says

Vendored from mattpocock/skills · MIT © 2026 Matt Pocock · upstream 6eeb81b · 已汉化并完成 VoidTech 插件内自包含适配。LICENSE 见 ../_vendor-licenses/mattpocock-LICENSE

本技能接收当前对话上下文与对代码库的理解,产出一份 PRD。不要访谈用户——只综合你已经掌握的内容。

与 prd-from-requirements 的分工

本技能适用于“从当前对话轻量整理一份单体 PRD,并发布到 issue 追踪器”,主要服务开发交付和后续 agent 实现。

如果用户提供的是原始需求文档、Excel 整理稿、访谈纪要、需求清单或旧版 PRD,并需要模块化 PRD 工作树、需求追溯矩阵、状态机、字段规则、权限矩阵、跨系统依赖或 product-manager subagent 评审,应改用 voidtech-product:prd-from-requirements

开始前读取 Issue 跟踪器适配契约,据此识别平台、认证和标签映射;不要求任何预先安装的初始化技能。

流程

  1. 如果尚未做过,先探查仓库以了解代码库的现状。在整份 PRD 中使用项目业务词汇表的词汇,并尊重你所触及区域内的任何 ADR。

  2. 勾勒出你将用来测试该功能的 seam。优先使用已有的 seam 而非新建。使用尽可能高的 seam。如果确需新的 seam,请在尽可能高的位置提出。跨代码库的 seam 越少越好——理想数量是一个。

若对话中已经确认 seam,把它作为决策记录;若尚未确认,把建议写成 Testing Decisions 中明确标注的 proposed decision。不要为此重新开启需求访谈。

  1. 使用下面的模板写出 PRD。

  2. 发布前使用 voidtech-core:text-naturalizer 的规则润色 PRD 正文,去掉模板腔、抽象话和 AI 写作痕迹。若 Skill 工具可用,调用 voidtech-core:text-naturalizer 处理草稿;若不可用,按本条规则自行审阅并改写,不从当前插件目录猜测 Core 的安装路径。润色时必须保留事实、范围、术语、标题层级、列表结构、实现决策、测试决策和不在范围内的内容,不得为了自然表达而弱化约束。

  3. 将润色后的 PRD 发布到项目的 issue 追踪器。使用 category enhancement 与 state ready-for-agent 对应的实际标签,无需再走 issue 整理流程。若跟踪器不可用,按适配契约生成完整 Markdown 草稿并返回路径。

问题

用户所面临的问题,从用户的视角出发。

方案

针对该问题的解决方案,从用户的视角出发。

用户故事

一份带编号的完整用户故事列表。每条用户故事应采用如下格式:

  1. 作为 <角色>,我希望 <功能>,从而 <收益>

这份用户故事列表应尽量覆盖该功能的主要使用场景。

实现决策

一份已做出的实现决策列表。可以包括:

  • 将要构建/修改的模块
  • 这些模块将被修改的接口
  • 来自开发者的技术澄清
  • 架构决策
  • Schema 变更
  • API 契约
  • 具体的交互

不要包含具体的文件路径或代码片段。它们可能很快就过时了。

例外:如果原型中的代码片段能更准确地表达某项决策(状态机、reducer、schema、类型结构),可以把它放在相关决策中,并注明来源。只保留表达决策所需的部分,不要附上完整演示。

测试决策

一份已做出的测试决策列表。包括:

  • 对什么是好测试的描述(只测试外部行为,不测试实现细节)
  • 哪些模块将被测试
  • 测试的先例(即代码库中类似类型的测试)

不在范围内

对本 PRD 范围之外内容的描述。

补充说明

关于该功能的任何补充说明。

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. yesterday First seen · 87 lines · 37 tokens per session scan A 9d541f16202d

Subscribe to this mod's changes

to-prd is a skill published in the GitHub repository VoidTechnology/voidtech-claude-plugins (2 stars, last pushed 28d ago), licensed Apache-2.0. It adds 37 tokens to every session and 1,103 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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