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 sutchan/Agent-Skills-Hub --skill opc-mvp-designergit clone --depth 1 https://github.com/sutchan/Agent-Skills-HubWrote 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/sutchan/agent-skills-hub/opc-mvp-designer)<a href="https://agentmods.dev/skills/sutchan/agent-skills-hub/opc-mvp-designer"><img src="https://agentmods.dev/badge/skills/sutchan/agent-skills-hub/opc-mvp-designer/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/sutchan/agent-skills-hub/opc-mvp-designer"><img src="https://agentmods.dev/badge/skills/sutchan/agent-skills-hub/opc-mvp-designer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00071 | $0.01353 |
| Opus 5 | $0.00036 | $0.00677 |
| Sonnet 5 | $0.00014 | $0.00271 |
| Haiku 4.5 | $0.00007 | $0.00135 |
Grade A, and why
opc-mvp-designer 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 8d 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 — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MVP 设计
目标
帮助用户确定“最先验证什么、用什么最小形式去验证”，而不是替用户直接定一个产品。
核心原则
- 默认读写当前工作目录下的
opc-doc/ - 教学模式下先解释 MVP 不是“简陋产品”，而是“最小验证”
- 默认一次只问一个问题；如果几个问题都很轻、彼此紧密相关，可以合并成 2 到 3 个
- 默认给 3 个 MVP 方案，并附加
4. 我有自己的方案 - 用户确认后再写入正式结果
- 不直接给推荐结论，只做方案分析
- 本阶段只做"验证什么、用什么最小形式验证"，不进入内容创作或交付细节
本阶段边界
本步做什么
- 确认最优先需要验证的假设
- 选定最小验证形式（服务先行 / 内容验证 / 工具原型等类别）
- 明确成功标准和 MVP 边界
本步不做什么（以下属于后续阶段，不要提前进入）
- ❌ 不写具体内容选题、文案或帖子（属于 opc-asset-ops）
- ❌ 不设计完整转化路径（属于 opc-conversion-loop）
- ❌ 不设计交付 SOP 或运营细节（属于 opc-asset-ops）
越界检测：如果出现"第一篇帖子写什么""具体怎么做这次验证""文案怎么写"等执行话题，先记录，再说：
"这些执行细节会在转化闭环和资产沉淀阶段处理。现在先把验证路径的框架确认好。"
本步骤必须完成什么
- 明确当前最先要验证的假设
- 明确最小验证形式
- 明确成功标准
- 明确 MVP 边界
- 明确人机分工
优先确认顺序
- 最优先验证的假设
- 最小验证形式
- 成功标准
- MVP 边界
- 人机分工
完成标准
- 已形成可执行的 MVP 方案
- 用户已确认当前主验证路径
本步需要解释什么
教学模式下先解释：
- MVP 的作用是验证假设
- 不是功能越多越好
- 一人公司更适合先跑通最小闭环
输入
优先读取：
opc-doc/outputs/04-business-model/risky-assumptions.md
如果依赖不完整，先建议回到 opc-business-model-design。
执行步骤
- 解释本步作用
- 默认一次只问一个问题；如果几个问题都很轻、彼此紧密相关，可以合并成 2 到 3 个，例如：
- 你最想先验证的假设是哪一个？
- 你更愿意用服务、内容还是工具来验证？
- 每轮回答后，给简短反馈
- 生成 3 个 MVP 方案，例如：
- 服务先行版
- 内容验证版
- 工具原型版
- 每个方案说明验证什么、适合什么情况、优点和代价
- 默认增加
4. 我有自己的方案 - 让用户选择、组合、修改，或直接提出自己的版本
- 用户确认后，再写入正式结果
输出
对话层必须包含：
- 本步解释
- 当前要验证的假设摘要
- 3 个 MVP 方案 +
4. 我有自己的方案 - 每个方案的适用情况、优点和代价
- 请用户确认或修改
落盘检查点（阶段必须完成，不可跳过）
用户明确确认 MVP 方案后，立即使用 Write 工具在文件系统上创建以下文件，然后才能进入下一阶段。在对话中描述结论不等于落盘。
写入文件：
opc-doc/outputs/06-mvp-design/mvp-spec.md（验证假设 + 最小验证形式 + MVP 边界）opc-doc/outputs/06-mvp-design/experiment-plan.md（成功标准 + 验证周期）opc-doc/outputs/06-mvp-design/human-ai-split.md（人工 vs AI 分工说明）
更新状态文件：
opc-doc/state/current-stage.json（写入：{"stage": "06-mvp-design", "status": "completed", "next_stage": "07-conversion-loop", "summary": "一句话 MVP 核心"}）opc-doc/state/assumptions.json（更新已验证/待验证假设状态）
落盘完成后，在对话中告知用户：
"✅ MVP 方案已保存。下次对话可以从转化闭环继续。"
只有落盘完成后，才可以提示进入 opc-conversion-loop。
何时调用其他 skills
只有在用户确认 MVP 方案后，才进入 opc-conversion-loop。
What ships with it
3 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.
- 8d ago First seen · 135 lines · 71 tokens per session scan A ae52b0e4e923
opc-mvp-designer is a skill published in the GitHub repository sutchan/Agent-Skills-Hub (2 stars, last pushed yesterday), licensed MIT. It adds 71 tokens to every session and 1,353 once invoked, about $0.0004 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 2026-09-04.
Other skills, from other repositories
writing-skills
Use when creating new skills, editing existing skills, or verifying skills work before deployment.
receiving-code-review
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation.
writing-plans
Use when you have a spec or requirements for a multi-step task, before touching code.
skill-authoring
Author SKILL.md skills: frontmatter, validator limits, structure.
skill-creator
Create, improve, evaluate, benchmark skills. Use when authoring a new skill, updating an existing one, running evals, or optimizing a skill's description for triggering. Don't use for invoking skills, writing prose, or scaffolding Python projects.
iflytek-hyper-tts
A text-to-speech tool that turns written text into an MP3 recording. It can use an authorized voice and adjust speaking speed, volume, and pitch.