solution-to-delivery

solution-to-delivery is a skill for Codex from PANGKAIFENG/ai-product-manager-skills. It costs 89 tokens per session (984 once invoked), scanned A, original, MIT.

A workflow for turning an approved product idea into reviewed delivery materials. It can include a product requirements document, interface mockups, version planning, and draft development tasks.

In plain words
What is it for?
Use it after a product solution is confirmed to prepare a reviewed delivery package, split work into versions, and run a final readiness check before publication.
Why use it?
It provides checks between the original idea, its requirements, interface evidence, and planned work. It also makes clear when human approval or missing information prevents the next step.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: mentions Codex; $skill-name invocation.

Good fit Use it after a product solution is confirmed to prepare a reviewed delivery package, split work into versions, and run a final readiness check before publication.

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Install with agentmods
npx agentmods add skills/pangkaifeng/ai-product-manager-skills/solution-to-delivery
Install

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.

Any agent
npx skills add PANGKAIFENG/ai-product-manager-skills --skill solution-to-delivery
Clone the repo
git clone --depth 1 https://github.com/PANGKAIFENG/ai-product-manager-skills

Made for: Codex.

Wrote 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.

agentmods badge for solution-to-delivery

README.md
[![agentmods](https://agentmods.dev/badge/skills/pangkaifeng/ai-product-manager-skills/solution-to-delivery/github.svg)](https://agentmods.dev/skills/pangkaifeng/ai-product-manager-skills/solution-to-delivery)
Your own site
<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.

agentmods 80×15 button for solution-to-delivery

Your own site · 80×15
<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>
Per session 89 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 984 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00089 $0.00984
Opus 5 $0.00044 $0.00492
Sonnet 5 $0.00018 $0.00197
Haiku 4.5 $0.00009 $0.00098

Measured 12d ago against content hash 5321ffc11b6a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

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 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.

workflows/solution-to-delivery/SKILL.md · 54 lines

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

  1. 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。
  2. 使用 prd-architect 生成 PRD,并初始化 Product Delivery Manifest。
  3. 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。
  4. 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。
  5. 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。
  6. 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。
  7. 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。
  8. 运行 Product Delivery validator,确保最终 Manifest、artifacts、生产者身份和 Review fingerprint 一致。
  9. 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。

Read the full file on GitHub · 54 lines

Files

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.

Changes

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.

  1. 12d ago First seen · 54 lines · 89 tokens per session scan A 5321ffc11b6a

Subscribe to this mod's changes

solution-to-delivery is a skill published in the GitHub repository PANGKAIFENG/ai-product-manager-skills (11 stars, last pushed 12d ago), licensed MIT. It adds 89 tokens to every session and 984 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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