A workflow for creating a PRD, or product requirements document, from a description or an existing file. The document records goals, users, requirements, non-functional needs, acceptance criteria, and links to related features.

Use it to create or structure requirements, assign a feature ID, apply project standards and templates, and prepare a handoff to the next development stage.

It turns informal requests into a consistent document that later design and development work can rely on. It can also detect possible links to existing features.

pdlc-prd — Skill for Claude Code by kanfu-panda

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.

Any agent

npx skills add kanfu-panda/pdlc-skills --skill pdlc-prd

Clone the repo

git clone --depth 1 https://github.com/kanfu-panda/pdlc-skills

Made for: Claude Code.

Or install pdlc, the plugin that ships this one along with the rest of its 38 skills.

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/kanfu-panda/pdlc-skills/pdlc-prd/github.svg)](https://agentmods.dev/skills/kanfu-panda/pdlc-skills/pdlc-prd)

Your own site

<a href="https://agentmods.dev/skills/kanfu-panda/pdlc-skills/pdlc-prd"><img src="https://agentmods.dev/badge/skills/kanfu-panda/pdlc-skills/pdlc-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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/kanfu-panda/pdlc-skills/pdlc-prd"><img src="https://agentmods.dev/badge/skills/kanfu-panda/pdlc-skills/pdlc-prd.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 22 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,635 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. Third-party audits

NVIDIA SkillSpector warn 7 Sept 2026

SkillSpector: 2 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

high Prompt Injection · line 19
Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.

Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
high Prompt Injection · line 19
Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.

Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.

How audits are shown

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.

Model	Per session	Once invoked
Fable 5.1	$0.00022	$0.01635
Opus 5	$0.00011	$0.00817
Sonnet 5	$0.00004	$0.00327
Haiku 4.5	$0.00002	$0.00163

Measured 12d ago against content hash 2afaaf113b29, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

pdlc-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 12d 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.

skills/pdlc-prd/SKILL.md · 137 lines

How it starts

The opening of the file, as written. The whole thing — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.

创建 PRD 文档

根据用户提供的需求描述或已有需求文档，在 docs/01_requirements/prd/ 目录下创建一份完整的 PRD（产品需求文档）。

段一：生成 PRD

1.1 输入解析（必须执行）

从 $ARGUMENTS 中判断输入类型：

检测是否为文件路径：匹配以下模式之一即视为文件输入：
- 以 /、./、../、~ 开头
- 以 .md、.txt、.docx、.pdf、.doc 结尾
- 包含 docs/ 或 requirements/ 路径片段
- 是一个实际存在的文件路径
文件输入处理：
- 读取文件内容（支持 Markdown、纯文本、PDF）
- 若为飞书文档链接，通过飞书 API 获取
- 从内容提取：功能名称、范围、用户故事、验收标准
- 保留原文档核心内容，仅补充和结构化，不重写
- 在 PRD 中添加：
文本输入处理：按描述推断功能需求

核心原则：文件输入是「基于已有内容结构化」，文本输入是「从零生成」。

1.2 功能ID分配

1.3 生成 PRD 文档

阅读 templates/prd-template.md 获取模板格式
阅读 docs/00_standards/coding/ 获取编码规范（若存在；查找未命中 → 在报告里提示 consider /pdlc-standard add coding/<topic>）
文件名格式：<功能ID>-<功能名>-prd.md
文档顶部加 PDLC 追溯头：

文档必须包含：背景与目标、目标用户、功能需求（含优先级）、非功能需求、验收标准

用户故事使用标准格式："作为[角色]，我希望[功能]，以便[收益]"

1.4 关系检测（RFC#6）

从输入检测 feature 关系信号：

关键词扫描：输入含「基于 / 扩展 / 增强 / based on / extends / 依赖 / 替代 / 修复缺陷」等 → 存在关系
扫描现有 feature：读 docs/.pdlc-state/*.json 列已有 feature 名，判断本 PRD 是否 extends/depends_on 其一
填 §6.1 关系表：识别到的关系填入模板「6.1 关系」表（类型/目标ID/目标名/原因）。无则留空
类型语义见 relations.md

Phase 2：本步从"被动检测"升级为"主动提示用户确认关系"。

1.5 核心流程挂钩（若项目已启用质量闸门）

若存在 docs/00_standards/quality-targets.yml：本 PRD 里标为 P0 / P1 的流程，逐条比对该文件的 core_flows，在 handoff 里提示补齐尚未收录的流程及其 E2E 映射。

为什么在这里提示：core_flows 清单若靠"事后有人记得改"来维护必然腐烂，而腐烂的清单会让质量报告产出 false-green（新增核心流没进清单 → 覆盖矩阵照样全绿）。 PRD 是这些流程的上游真源，在产出时就挂钩，比事后补救可靠。 /pdlc-quality 每次运行还会再做一次强制对账兜底。

段二：自检（强制）

PRD 自检清单（必须全部检查）

完整性：

背景与目标：清晰说明为什么做、业务价值是什么
目标用户：至少一类用户角色定义明确
用户故事：≥ 3 条且符合标准格式
功能清单：每条有 P0/P1/P2 优先级标注
验收标准：可度量、可验证（有具体数值或明确通过/不通过条件）
非功能需求：至少覆盖性能、安全、可用性中的两项

Read the full file on GitHub · 137 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.

12d ago First seen · 137 lines · 22 tokens per session scan A 2afaaf113b29

Subscribe to this mod's changes

pdlc-prd is a skill published in the GitHub repository kanfu-panda/pdlc-skills (13 stars, last pushed today), licensed MIT. It adds 22 tokens to every session and 1,635 once invoked, about $0.0001 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.

Claude Code Planning Writing and docs agentic-workflow ai-agent ai-coding claude-plugin claude-skills

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