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 mileson/openprd --skill openprd-learning-reviewgit clone --depth 1 https://github.com/mileson/openprdWrote 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/mileson/openprd/openprd-learning-review)<a href="https://agentmods.dev/skills/mileson/openprd/openprd-learning-review"><img src="https://agentmods.dev/badge/skills/mileson/openprd/openprd-learning-review.svg" alt="Measured on agentmods" 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 | $0.00048 | $0.01413 |
| Opus 5 | $0.00024 | $0.00707 |
| Sonnet 5 | $0.00010 | $0.00283 |
| Haiku 4.5 | $0.00005 | $0.00141 |
Grade A, and why
openprd-learning-review 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 4d 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenPrd Learning Review
何时使用
当用户希望把 OpenPrd 工作区、已完成的 loop 任务，或某个项目领域整理成复盘学习包时，使用这份 skill。不要用关键词表触发；先看用户目标和期望产物形态。
- 长任务结束，或某个已验证 loop 任务刚完成
- 当前交付需要章节结构、证据锚点、图文讲解、检索练习、工作示例或长期阅读体验；这类形态默认优先走学习包和阅读器，不要只交一篇普通 Markdown
- 用户明确要求复盘某个项目领域或能力面
- 需要构建或刷新题材模板、证据清单、检索模块或工作示例
- 需要生成归档在
.openprd/内的 HTML 电子书阅读器 - 需要把已验证修复或质量复盘连接到可复用的项目经验；此时让 Skill 产物继续经过
$openprd-quality，把抽象模式沉淀到.openprd/knowledge/skills/ - 需要区分“项目经验沉淀”和“操作配置自我成长”；配置缺口、文件识别、命令习惯或用户偏好应进入
.openprd/growth候选，而不是直接写入学习包或共享 Skill
核心契约
- 严格分离五层：证据清单、无风格学习内容契约、风格提示词包、带风格学习内容、HTML 阅读器。图文比喻卡和图片提示属于内容契约的一部分，不单独分叉渲染器。
- 默认模式由配置开启；即使自动模式关闭，手动生成也必须可用。
- 学习包统一归档到
.openprd/learning/archive/<packageId>/。 - 项目级预防 Skill 单独放在
.openprd/knowledge/skills/，不要把复发预防规则只埋在学习电子书里。 .openprd/growth/只保存待确认配置、规则和偏好候选；经用户确认后才固化为项目共享配置或 user-local 偏好。- 每一条结论都必须能追溯到 source id、路径、摘录和 digest。
- 除专门的 Markdown 阅读稿外，不要把叙事正文和 provenance 元数据混在同一个文件里。
工作流程
- 从
.openprd/state/current.json、.openprd/state/task-graph.json、当前 PRD 产物、docs/basic和最近的 loop 报告重建上下文。 - 选择主题、题材和可选子风格。默认使用
internet-product；对xianxia默认使用cultivation提示词包。 - 先构建
evidence-manifest.json。凡是无法追溯的句子，都标成推断。 - 先生成中性的
learning-content.json，再加载风格提示词包并运行 Agent-in-the-loop 风格迁移；对产品或非技术读者优先补visualExplainer图文比喻卡。 - 在内容契约里记录提示词包 id、提示词文本、风格迁移报告、图文讲解字段和质量检查结果。
- 把
reader.html渲染为固定电子书界面：有书式目录、章节分页、正文独立滚动、进度、上一章/下一章、字体控制、章节级 source 锚点，以及章节内可选的图文比喻卡与图片槽位。不要把单个检索题放进目录。 - 把
learning-package.json、learning-content.json、learning-content.md、evidence-manifest.json和reader.html一起写入归档目录。 - 更新
.openprd/learning/index.json和.openprd/learning/current.json，让后续任务能快速找到最新学习包。 - 当配置允许自动打开时，在学习包创建后自动打开阅读器。
- 如果学习包记录的是已验证修复、重复问题、隐藏调试路径或 Agent 误判，运行或建议运行
openprd quality <path> --learn --from <eval-report>，把抽象模式沉淀成未来可触发的项目 Skill。
章节结构
每个学习包都尽量覆盖这些模块：
- 解释学习包为何存在的叙事开场
- 点名相关
.openprd/文件和工作流状态的系统地图章节 - 帮助产品或非技术读者先建立直觉的图文比喻卡
- 区分事实、claim 和推断的 provenance 章节
- 让读者回忆关键机制的检索模块
- 展示如何迁移到新场景的工作示例模块
- 告诉读者下一步做什么的收束章节
扩展规则
- 新增题材时，扩展题材参考库，不要分叉渲染器。
- 内容契约必须版本化；当结构变化时，引入新的 schema 版本。
- 即使文风变化，证据清单中的 source id 和路径也必须保留。
- 保持 HTML 阅读器稳定，确保历史归档学习包在未来仍可重新打开。
What ships with it
9 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.
- agents/openai.yaml 335 B
- references/content-contract.md 2.8 KB
- references/ebook-reader.md 1.7 KB
- references/evidence-manifest.md 1.0 KB
- references/genre-library.md 2.2 KB
- references/prompt-engineering.md 1.9 KB
- references/quality-rubric.md 1.2 KB
- references/retrieval-worked-example.md 1.1 KB
- references/style-packs/xianxia-cultivation.prompt.md 2.2 KB
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.
- 4d ago First seen · 77 lines · 48 tokens per session scan A 91a04aace6d2
openprd-learning-review is a skill published in the GitHub repository mileson/openprd (50 stars, last pushed 9d ago), licensed MIT. It adds 48 tokens to every session and 1,413 once invoked, about $0.0002 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 2026-09-03.
Other skills, from other repositories
openspec-onboard
Guided onboarding for OpenSpec - walk through a complete workflow cycle with narration and real codebase work.
openspec-bulk-archive-change
Archive multiple completed changes at once. Use when archiving several parallel changes.
openspec-explore
Enter explore mode - a thinking partner for exploring ideas, investigating problems, and clarifying requirements. Use when the user wants to think through something before or during a change.
openspec-sync-specs
Sync delta specs from a change to main specs. Use when the user wants to update main specs with changes from a delta spec, without archiving the change.
openspec-archive-change
Archive a completed change in the experimental workflow. Use when the user wants to finalize and archive a change after implementation is complete.
openspec-ff-change
Fast-forward through OpenSpec artifact creation. Use when the user wants to quickly create all artifacts needed for implementation without stepping through each one individually.