requirement-analysis

requirement-analysis is a skill for Claude Code, Codex from protect-my-hair/nucleus-marketplace. It costs 32 tokens per session (3,151 once invoked), scanned A, original, MIT.

A process for deciding whether a requested software change is clear enough to accept and whether its cost can be trusted. It can produce draft product requirements and an evaluation for review, but does not design or implement the feature.

In plain words
What is it for?
Use it to clarify a request, assess how well it fits the product, identify gaps and a possible path, estimate effort, and recommend whether to accept it. It requires reading the request and relevant product and feature context first.
Why use it?
It prevents teams from estimating or accepting vague work before key questions are answered. It separates requirement assessment from feature design, development planning, testing, and final approval.

Skill for Claude CodeCodex

Written for Claude Code and Codex: SessionStart hook event, but also agents/openai.yaml present. Also seen: names the TodoWrite tool; mentions Claude Code; mentions Codex.

Part of the nucleus plugin — 27 skills, 1 agent, 1 hook shipped together

Good fit Use it to clarify a request, assess how well it fits the product, identify gaps and a possible path, estimate effort, and recommend whether to accept it. It requires reading the request and relevant product and feature context first.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/protect-my-hair/nucleus-marketplace/requirement-analysis
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 protect-my-hair/nucleus-marketplace --skill requirement-analysis
Clone the repo
git clone --depth 1 https://github.com/protect-my-hair/nucleus-marketplace

Made for: Claude Code, Codex.

Or install nucleus, the plugin that ships this one along with the rest of its 27 skills, 1 agent, 1 hook.

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 requirement-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/protect-my-hair/nucleus-marketplace/requirement-analysis/github.svg)](https://agentmods.dev/skills/protect-my-hair/nucleus-marketplace/requirement-analysis)
Your own site
<a href="https://agentmods.dev/skills/protect-my-hair/nucleus-marketplace/requirement-analysis"><img src="https://agentmods.dev/badge/skills/protect-my-hair/nucleus-marketplace/requirement-analysis/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 requirement-analysis

Your own site · 80×15
<a href="https://agentmods.dev/skills/protect-my-hair/nucleus-marketplace/requirement-analysis"><img src="https://agentmods.dev/badge/skills/protect-my-hair/nucleus-marketplace/requirement-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,151 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 pass 7 Sept 2026
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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00032 $0.03151
Opus 5 $0.00016 $0.01576
Sonnet 5 $0.00006 $0.00630
Haiku 4.5 $0.00003 $0.00315

Measured 12d ago against content hash ab196a29636b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

requirement-analysis 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.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/requirement_analysis.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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/nucleus/skills/requirement-analysis/SKILL.md · 165 lines

How it starts

The opening of the file, as written. The whole thing — 165 lines — stays where its author put it; the contents beside it link to each section on GitHub.

需求分析

前置:使用本 Skill 前,先按 using-nucleus 完成 Nucleus 入口识别(Claude Code 会话由插件 SessionStart hook 自动注入该纪律)。

核心原则

关键澄清没有回答前,只能澄清,不能估算,不能建议接纳。

需求分析只回答“需求是否清楚、是否值得接纳、接纳成本是否可信”。它可以产出待评审 PRD、满足度 / 工作量评估、需求尺寸和接纳建议,但不做需求设计、正式特性拆解、开发计划、测试计划、技术方案、源码修改或最终接纳裁决。

待评审 PRD 和 evaluation 草稿提交人工或 PMS 评审前,必须先按 requirement-analysis-reviewsubagentPreReview 调度独立 reviewer 子代理;未取得“材料可提交人工审查”预审结论时,不得请求人工评审通过。

什么时候使用

使用本 Skill:

  • 判断一个需求是否清楚、是否值得接纳、接纳成本是否可信。
  • 生成供产品经理或 PMS 评审的 docs/requirement/**/prd.mdevaluation.md 草稿。
  • 在明确授权下把澄清、满足度、gap、满足路径、轻量实现口径、工作量、需求尺寸和接纳建议收口为需求分析证据。

不要使用本 Skill:

  • 已接纳需求后的方案设计、产品子需求拆解或正式特性拆解。
  • 特性设计、开发准备、测试生成、缺陷修复或交付收口。
  • 普通 setup、普通开发或未授权场景写 docs/requirement/**

Checklist

启动本 Skill 后,必须先为每一项创建宿主 todo/task,并按顺序逐项推进、逐项更新状态;Codex 使用计划 / 任务工具,Claude Code 使用 TodoWrite 或等价宿主 todo。.nucleus/runs/**summary.mdresult.json、候选文件和 review report 只能记录事实,不能替代宿主任务、人工回答、人工评审或 PMS 接纳事实。

  1. 读取需求输入和 context 完成证据:input-evidence.json 或等价输入证据。 STOP:未读需求输入、.nucleus/context/<workflowRunId>.json 或 standalone problem statement 时,不得提问、估算或生成需求文档。

  2. 读取产品上下文 完成证据:产品定位、docs/features/**docs/architecture/**、安全实现线索或缺失证据。 STOP:未读产品与特性上下文时,不得把用户原话直接整理成 PRD。

  3. 复述当前理解 完成证据:understanding.md,说明需求想解决什么、归属哪个产品能力、已有满足度初判和证据缺口。 STOP:复述中出现技术方案、接口设计、数据表、权限码或开发计划时,必须退回需求语言。

  4. 识别并推动关键澄清 完成证据:clarification-questions.jsonclarification-candidate.md、人工回答记录。 STOP:一次只能推动一个最影响接纳和成本的问题;没有明确回答前,不得生成 PRD、工作量或接纳建议。细节读取 references/clarification-method.md

  5. 调用 requirement-evaluation 做满足度和工作量评估 完成证据:analysis-package.jsonworkload-estimate.jsonacceptance-recommendation.json 或等价结构化评估证据。 STOP:必须显式加载并执行 requirement-evaluation;形成满足度 gap、满足路径、轻量实现口径和工作量评估前,不得估人日、不得给接纳建议、不得写需求评估正文;不得直接从澄清答案跳到人日估算。

  6. 调用 requirement-sizing 识别需求尺寸 完成证据:requirement-sizing.json,以及待写入 evaluation.md 的“需求尺寸”中文结论。 STOP:需求尺寸必须在满足度、gap、满足路径、轻量实现口径和工作量评估完成后识别;不得在需求澄清开始阶段、单凭原始需求标题或早期澄清问题猜测尺寸。

Read the full file on GitHub · 165 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. 12d ago First seen · 165 lines · 32 tokens per session scan A ab196a29636b

Subscribe to this mod's changes

requirement-analysis is a skill published in the GitHub repository protect-my-hair/nucleus-marketplace (162 stars, last pushed 1mo ago), licensed MIT. It adds 32 tokens to every session and 3,151 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 2026-08-30.

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