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 problem-to-solutiongit 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/problem-to-solution)<a href="https://agentmods.dev/skills/pangkaifeng/ai-product-manager-skills/problem-to-solution"><img src="https://agentmods.dev/badge/skills/pangkaifeng/ai-product-manager-skills/problem-to-solution/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/problem-to-solution"><img src="https://agentmods.dev/badge/skills/pangkaifeng/ai-product-manager-skills/problem-to-solution.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 | $0.00083 | $0.00663 |
| Opus 5 | $0.00042 | $0.00331 |
| Sonnet 5 | $0.00017 | $0.00133 |
| Haiku 4.5 | $0.00008 | $0.00066 |
Grade A, and why
problem-to-solution scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
问题到方案
这是 workflow 的 Codex Runtime 入口，不是新的原子 Skill。先读取同目录 WORKFLOW.md，再按当前状态调用现有 Skill 或 Loop。
输入
优先从对话和项目材料中发现以下信息，只询问会改变路线的缺口：
- 当前问题或模糊感受；
- 期望结果与判断标准；
- 用户、业务场景、约束和截止时间；
- 已有事实、候选方案和不可改变项。
工作流
- 先判断输入状态：问题、目标或判断标准不稳定时使用
ai-collaboration-calibration；已经稳定时跳过校准。 - 只有当事实缺口会改变选择时才进入研究：开放式领域理解使用
research-topic-compiler，具体选择缺证据时使用$decision-loop。 - 问题已稳定但没有候选方案时，直接使用
brainstorming比较真实方案并形成推荐与 Design Spec。 - 已有候选方案且只需挑战时，直接进入
$solution-loop；其他情况只在方案风险、依赖或失败模式需要多轮关闭时进入。 - 按
WORKFLOW.md的 Confirmed Solution Gate 判断结束、Human Gate 或阻塞，不用文档数量代替方案确认。
边界
- 不为了走流程而调用全部 Skill。
- 不把研究结论直接伪装成产品方案。
- 不让 Maker 自己声明挑战已经关闭。
- 不生成完整 PRD、UI 交付包、研发事项或外部发布结果。
- Skill/Loop handoff 不授权 DingTalk、Yunxiao、Runtime 或 Skillshare 写入。
输出
返回 status、稳定的问题定义、关键决策、已确认方案、保留项、剩余 gap、下一责任节点和恢复点。只有达到 solution_confirmed 才建议进入 $solution-to-delivery。
完成定义
只有 WORKFLOW.md 的 Confirmed Solution Gate 全部成立，且需要业务取舍时已经经过 Human Gate，才输出 solution_confirmed。否则必须返回唯一 next_gap 和可恢复的 resume_point。
资源与验证
WORKFLOW.md是阶段路由、完成门槛和输出状态的权威合同，每次执行前读取。evals/evals.json覆盖完整路径、最短路径、相邻原子 Skill 和下游 Workflow 的触发回归；修改入口后运行这些评测并保留结果。
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.
- 12d ago First seen · 49 lines · 83 tokens per session scan A 5851a8203638
problem-to-solution is a skill published in the GitHub repository PANGKAIFENG/ai-product-manager-skills (11 stars, last pushed 12d ago), licensed MIT. It adds 83 tokens to every session and 663 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 2026-08-31.
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