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 solution-to-deliverygit 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/solution-to-delivery)<a href="https://agentmods.dev/skills/pangkaifeng/ai-product-manager-skills/solution-to-delivery"><img src="https://agentmods.dev/badge/skills/pangkaifeng/ai-product-manager-skills/solution-to-delivery/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/solution-to-delivery"><img src="https://agentmods.dev/badge/skills/pangkaifeng/ai-product-manager-skills/solution-to-delivery.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 | $0.00089 | $0.00984 |
| Opus 5.5 | $0.00036 | $0.00394 |
| Sonnet 5.5 | $0.00018 | $0.00197 |
| Haiku 4.5 | $0.00009 | $0.00098 |
Grade A, and why
solution-to-delivery 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 1mo 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 — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.
方案到交付
这是 workflow 的 Codex Runtime 入口，不是新的原子 Skill。先读取同目录 WORKFLOW.md，再编排现有 PRD、UI、Review、Issue 和 Tool 能力。
输入
优先发现已确认方案、项目目录、现有 PRD/UI、交付目标和版本要求。缺少会改变交付形态的信息时才询问：
- 方案目标、范围、关键流程、约束和已知风险；
- 是否存在用户可见界面；
- 交付到研发、钉钉、GitHub、云效或仅本地；
- 是否需要 V1/V2/V3 或研发事项拆分。
工作流
- 检查方案是否达到 Entry Gate；未达到则交回
$problem-to-solution，不自行补写假方案。 - 使用
prd-architect生成 PRD，并初始化 Product Delivery Manifest。 - 有用户可见界面时使用
ui-mockup-desktop-workbench生成目标态 HTML/预览与关键状态截图；无界面时记录可审计的不适用理由。 - 为所有 PRD/UI artifact 写入实际
producer_identity，再由独立prd-review检查 PRD 与适用 UI 证据，并把当前 fingerprint、覆盖的 Maker identities 和结论写入pre_split_review；未达到ready时只修阻断项，禁止生成版本计划或事项草稿。 - Validator 证明
pre_split_review仍为 current/ready 后，用户要求版本或研发拆分时才使用prd-to-issues生成版本计划、事项草稿和 PRD 覆盖矩阵；未经批准不发布。 - 把版本拆分产物写入 Manifest；Backlog Splitter 必须用 actor-scoped validator 把当前 identity 绑定到每项规划产物，再更新文件 hash 和 package fingerprint。
- 使用
$delivery-loop对这份完整 Package 做最终独立 Review；最终 Reviewer 必须覆盖全部 artifact producers 且与其身份独立，循环到package_ready、Human Gate 或阻塞。 - 运行 Product Delivery validator，确保最终 Manifest、artifacts、生产者身份和 Review fingerprint 一致。
- 用户要求发布时，交给 Package Publisher 做完整 dry-run；当前 Agent Runtime 无可信 host approval capability，真实写入保持
status: package_ready并返回publish_status: authorization_required。不得改走 Legacy direct mode 绕过 Package 合同。
边界
- 不重新讨论已经确认且未被新证据推翻的方案。
- 不把 HTML/截图伪装成生产实现。
- 不让 PRD Maker 自评 ready。
- 不让 UI Producer、Backlog Splitter 或其他 artifact Producer 自评或从 Review 覆盖范围中被省略。
- 不在独立 PRD readiness Review 通过前生成版本或事项拆分。
- 不因为 Workflow 或 Manifest approval 被创建就发布钉钉、创建云效事项或同步 Runtime；Package 真实写入等待可信宿主能力。
输出
返回交付状态、Package 根目录、PRD、适用的 UI/HTML/截图、Review verdict、版本计划、Manifest、发布状态、剩余 gap 和恢复点。
完成定义
只有 WORKFLOW.md 的 Delivery Ready Gate 全部成立，独立 Review 没有 P0/P1，且 Manifest 与当前 artifacts/producer identities 一致，才输出 package_ready。Package dry-run 可以验证发布输入；真实写入在当前 Agent Runtime 始终保持 authorization_required，不改变 Package readiness。
资源与验证
WORKFLOW.md是交付路由、适用产物和 readiness gate 的权威合同，每次执行前读取。evals/evals.json覆盖 UI、无 UI、单点 PRD、上游退回和外部授权回归；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.
- 1mo ago First seen · 54 lines · 89 tokens per session scan A 5321ffc11b6a
solution-to-delivery is a skill published in the GitHub repository PANGKAIFENG/ai-product-manager-skills (16 stars, last pushed 1mo ago), licensed MIT. It adds 89 tokens to every session and 984 once invoked, about $0.0004 per session on Opus 5.5. 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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