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.
npx skills add protect-my-hair/nucleus-marketplace --skill feature-development-preparegit clone --depth 1 https://github.com/protect-my-hair/nucleus-marketplaceWrote 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.
[](https://agentmods.dev/skills/protect-my-hair/nucleus-marketplace/feature-development-prepare)<a href="https://agentmods.dev/skills/protect-my-hair/nucleus-marketplace/feature-development-prepare"><img src="https://agentmods.dev/badge/skills/protect-my-hair/nucleus-marketplace/feature-development-prepare/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.
<a href="https://agentmods.dev/skills/protect-my-hair/nucleus-marketplace/feature-development-prepare"><img src="https://agentmods.dev/badge/skills/protect-my-hair/nucleus-marketplace/feature-development-prepare.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00026 | $0.02687 |
| Opus 5 | $0.00013 | $0.01344 |
| Sonnet 5 | $0.00005 | $0.00537 |
| Haiku 4.5 | $0.00003 | $0.00269 |
Grade A, and why
feature-development-prepare 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 13d 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.
How it starts
The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
特性开发准备
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
实施计划必须绑定当前阶段真实依赖;它不是脱离 primary feature、特性文档、需求输入和已存在 UI 设计源的普通任务清单。
生成实施计划前必须扫描目标仓库 docs/specs/** 规范事实源,并把适用 rules、缺失 rules 或 setup gap 写入 developmentSpecs;缺失规范不得被静默当作“无要求”。
生成实施计划前必须把 primary feature、需求输入、docs/specs/** 和 UI 设计源发现结果固化为 .nucleus/runs/<workflowRunId>/spec-anchor.json;实施计划必须包含 specAnchor,声明 facts manifest hash、reload policy、pre-edit gate 和 completion gate,供上下文压缩 / 恢复 / 阶段切换后重读。
发现 docs/ui-design/**/*.pen、docs/ui-design/**/ui-prototype.md 或用户 / context 明确提供 UI 设计源时,实施计划必须先区分“当前特性相关设计源”和“仓库候选设计源”;相关设计源必须把 UI 设计源、Pencil frame / UI 状态映射、公共组件 / 公共样式契约和视觉证据路径写成阻塞型验收项;候选设计源必须进入人工计划确认,未确认相关性前不得写 UI 源码。
请求开发计划人工评审前,必须先按 _shared/references/subagent-precheck-protocol.md 执行 subagentPreReview 子代理预审;未取得“材料可提交人工审查”预审结论时,不得请求人工批准计划。
什么时候使用
使用本 Skill:
- 在当前阶段 context 中已有恰好一个 primary feature,且
docs/features/**/feature.md与需求 / 拆解输入可读时,为该特性准备实施计划。 - 生成回链到 primary feature、特性文档和需求 / 拆解输入的可评审实施计划:Markdown 是人工计划主入口,JSON 是机器事实源和下游输入。
不要使用本 Skill:
- 当前特性文档缺失、需求 / 拆解输入缺失、没有明确单一 primary feature 时。
- 改源码、测试、特性文档、需求文档,或提交、推送、创建 PR/MR、关闭缺陷。
- 把计划写成脱离特性文档的独立 coding checklist。
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;Claude Code 用 TodoWrite 或等价宿主 todo,Codex 用计划 / 任务工具。.nucleus/runs/**、summary.md、result.json 只能记录事实,不能替代宿主任务、人工计划确认或人工评审事实。
-
读取 context 和输入 完成证据:已读
.nucleus/context/<workflowRunId>.json,以及声明 read-only 的需求方案 artifact。 STOP:未读 context 或需求拆解输入时,不得生成任何计划。 -
校验恰好一个 primary feature 且 feature.md 存在 完成证据:context 中恰好一个
features[].role=primary,且其docs/features/**/feature.md已存在。 STOP:缺 primary、多于一个 primary,或 primary feature 文件不存在时,返回FAILED_BLOCKED。 -
校验需求 / 拆解输入可读 完成证据:需求 / 拆解输入 artifact 存在、路径合法、read-only 且已记录 hash。 STOP:输入缺失、不可读、路径越界或写策略不符合边界时,
ALERT_AND_BLOCK。
What ships with it
8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/openai.yaml 571 B
- assets/feature-development-plan-template.json 5.0 KB
- assets/feature-development-plan-template.md 6.0 KB
- assets/nucleus-feature-development-plan.schema.json 20 KB
- references/blocker-matrix.md 597 B
- references/plan-schema.md 3.2 KB
- references/requirement-read-boundary.md 497 B
- scripts/feature_development_prepare.py 76 KB runs code
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.
- 13d ago First seen · 129 lines · 26 tokens per session scan A 58a7f8596f32
feature-development-prepare is a skill published in the GitHub repository protect-my-hair/nucleus-marketplace (162 stars, last pushed 1mo ago), licensed MIT. It adds 26 tokens to every session and 2,687 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 2026-08-30.
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