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 PANGKAIFENG/ai-product-manager-skills --skill brainstorminggit clone --depth 1 https://github.com/PANGKAIFENG/ai-product-manager-skillsWrote 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/pangkaifeng/ai-product-manager-skills/brainstorming)<a href="https://agentmods.dev/skills/pangkaifeng/ai-product-manager-skills/brainstorming"><img src="https://agentmods.dev/badge/skills/pangkaifeng/ai-product-manager-skills/brainstorming/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/pangkaifeng/ai-product-manager-skills/brainstorming"><img src="https://agentmods.dev/badge/skills/pangkaifeng/ai-product-manager-skills/brainstorming.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 | $0.00171 | $0.03122 |
| Opus 5 | $0.00086 | $0.01561 |
| Sonnet 5 | $0.00034 | $0.00624 |
| Haiku 4.5 | $0.00017 | $0.00312 |
Grade A, and why
brainstorming 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.
How it starts
The opening of the file, as written. The whole thing — 210 lines — stays where its author put it; the contents beside it link to each section on GitHub.
设计脑暴（brainstorming）
中文速查
- 中文名：设计脑暴 / 实现前方案校准
- 英文稳定名：
brainstorming - 分类：产品与 PRD / 认知与协作之间的方案收敛桥
- 状态：
core - 你可以这样叫我：
先脑暴一下方案、先不要写 PRD，帮我设计几种路径、参考 brainstorming 把这个需求变成设计 spec、实现前先讨论设计 - 适合：问题基本成立，但还没确定产品方案、信息架构、交互路径、技术切分或交付 spec，需要先探索 2-3 个可选设计并得到用户确认
- 不适合：问题还没定义清楚，改用
ai-collaboration-calibration；已有明确方案要被拷问，改用grill-me；已经要写正式 PRD，改用prd-architect
Overview
使用这个 Skill 把“可讨论的想法”推进成“可交付给 PRD、mockup 或开发计划的设计 spec”。它强调先理解上下文、逐步澄清、提出多个方案、确认设计，再进入下游 artifact。
它的默认下游可以是 prd-architect、ui-mockup-desktop-workbench、prd-to-issues 或实现计划；如果方案涉及 UI/mockup/HTML 可视化，必须先对齐项目已有视觉语言，避免生成与真实产品割裂的通用页面。需要反复压测时显式进入 $solution-loop，而不是创建新的方案 mega Skill。
本 Skill 是方案 Maker：拥有真实备选、推荐与取舍、scope、流程、状态、风险和 Design Delta；不拥有 Critic clearance、PRD/实现 readiness 或发布审批。
Boundary
先判断用户当前阶段：
- 问题、目标用户、成功标准或约束还不清楚：转
ai-collaboration-calibration，不要急着给方案。 - 问题已基本成立，但方案、路径、范围、交互或系统设计还没定：使用
brainstorming。 - 用户已经有一个具体方案，想找漏洞、压测失败模式或挑战取舍：转
grill-me。 - 用户明确要 PRD 文档、PRD 模板、PRD 图示或正式需求章节：转
prd-architect。 - 用户已有 PRD/handoff，要判断能否开发、可测试、可交付：转
prd-review。 - 用户已有 PRD 和 UI 规范，要真实桌面端 mockup：转
ui-mockup-desktop-workbench。 - Product Work Graph 的方案发散节点：使用 PUBLIC unqualified
brainstorming。只有用户显式调用完整名称superpowers:brainstorming时才走该 plugin Skill；不得从未限定的 “brainstorming” 推断它。
Hard Gate
在用户确认设计前，不要做以下事情：
- 不写生产代码。
- 不创建完整 PRD。
- 不生成正式 GitHub issues。
- 不把方案包装成已经确定的结论。
- 不进入 Superpowers
writing-plans或其他实现计划。
简单需求也要经过轻量设计确认。确认可以很短，例如：“我建议按方案 B 做，范围只包含 X/Y，不做 Z。你确认后我再写 PRD-lite。”
Workflow
- 复述目标和阶段：用一句话说明用户想解决的问题，以及当前是“方案脑暴”而不是执行。
- 读取可发现上下文：如果有 PRD、调研文档、代码、截图、UI 规范或历史讨论，先读；不要把可查信息问给用户。UI/mockup 相关任务还要读取
references/visual-design-standards.md。 - 判断是否需要转路由：按
Boundary决定是否继续本 Skill。 - 澄清关键缺口：一次只问一个会改变方案的问题。优先问目标用户、成功标准、边界、约束、已有资产和不可接受方案。
- 提出 2-3 个方案：每个方案必须包含适用前提、优点、代价、失败风险和不选理由。
- 给出推荐方案：明确推荐哪一个，或者推荐组合方案，并说明理由。
- 分段确认设计：按“范围 / 核心流程 / 信息结构或系统结构 / 异常与人工介入 / 验收口径”拆开确认。复杂设计可以逐段问用户是否认可。
- 输出设计 spec：根据任务复杂度输出轻量或标准 spec。需要写文件时，先确认保存位置；默认不强制创建特定目录。UI/mockup 相关 spec 必须包含项目视觉规范发现摘要，或说明启用的默认视觉标准。
- 自检 spec：检查 TBD、矛盾、范围漂移、双关要求、缺少验收标准和未关闭待确认项。
- 交接下游：按用户目标建议下一步：写 PRD、做 mockup、压测方案、拆 issues 或进入实现计划。
What ships with it
6 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.
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 · 210 lines · 171 tokens per session scan A d24af44da188
brainstorming is a skill published in the GitHub repository PANGKAIFENG/ai-product-manager-skills (11 stars, last pushed 13d ago), licensed MIT. It adds 171 tokens to every session and 3,122 once invoked, about $0.0009 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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