Borrowing it
Nothing to install: this file belongs to DavidLam-oss/obsidian-wechat-converter. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/DavidLam-oss/obsidian-wechat-converter/main/.claude/skills/openprd-learning-review/SKILL.mdgit clone --depth 1 https://github.com/DavidLam-oss/obsidian-wechat-converterWrote 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/davidlam-oss/obsidian-wechat-converter/openprd-learning-review)<a href="https://agentmods.dev/skills/davidlam-oss/obsidian-wechat-converter/openprd-learning-review"><img src="https://agentmods.dev/badge/skills/davidlam-oss/obsidian-wechat-converter/openprd-learning-review/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/davidlam-oss/obsidian-wechat-converter/openprd-learning-review"><img src="https://agentmods.dev/badge/skills/davidlam-oss/obsidian-wechat-converter/openprd-learning-review.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00039 | $0.00840 |
| Opus 5 | $0.00019 | $0.00420 |
| Sonnet 5 | $0.00008 | $0.00168 |
| Haiku 4.5 | $0.00004 | $0.00084 |
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 6d 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
OpenPrd Learning Review
当用户希望生成复盘学习包、题材模板库、证据清单、图文讲解模块、检索模块、工作示例或 OpenPrd 工作区里的 HTML 电子书阅读器时，使用这份 skill。 当用户目标是学习、复盘、教学、经验沉淀或把一次工作转成可长期阅读的材料时，先判断期望产物是否需要章节结构、证据锚点、图文讲解、检索练习或阅读体验；需要时默认走这条路径。普通 Markdown 可以作为讲义补充，但不能替代阅读器；这个判断基于场景和产物形态，不基于关键词表。 即使用户只说“请生成一份仙侠风格的学习材料”这类短请求，也先把它理解成学习型交付物；仙侠、科幻、童话等风格是题材/文体参数，不能成为绕过学习包和阅读器流程、只在聊天里写普通文章的理由。
产出物
learning-content.json：版本化内容契约evidence-manifest.json：source id、digest、摘录、claim 和缺口learning-content.md：书籍式阅读稿reader.html：固定电子书阅读器界面，支持章节级visualExplainer图卡assets/：可选图片素材目录，用于归档 Codex Image 2 生成的图文解释图片learning-package.json和.openprd/learning/index.json：归档元数据
工作流程
- 从
.openprd/重建状态，并识别触发源是 loop finish 还是手动请求。 - 从参考库里选择题材。主题没有特殊要求时，默认使用
internet-product。 - 写正文前先从工作区状态、
docs/basic和 loop 报告收集证据。 - 分离证据清单、叙事正文和渲染器；所有判断都必须能引用 source id。面向产品或非技术读者时，优先补
visualExplainer图卡。 - 尽可能在每章加入检索模块、工作示例模块和必要的图文比喻卡。
- 把学习包归档到
.openprd/learning/archive/<packageId>/，并在合适时打开reader.html。
扩展规则
- 新增题材时扩展参考库，不要分叉渲染器。
- 契约必须版本化；
openprd.learning-content.v1的演进要通过新版本完成。 - 任何无法追溯到来源的句子都要显式标为推断。
- 把阅读器保持为稳定的 HTML 电子书界面，包含 TOC、进度、上一章/下一章控制、章节内轻量证据锚点和可选图文解释卡。
参考资料
skills/openprd-learning-review/references/genre-library.mdskills/openprd-learning-review/references/content-contract.mdskills/openprd-learning-review/references/evidence-manifest.mdskills/openprd-learning-review/references/ebook-reader.mdskills/openprd-learning-review/references/retrieval-worked-example.mdskills/openprd-learning-review/references/quality-rubric.md
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.
- 6d ago First seen · 52 lines · 39 tokens per session scan A 36ac0b870cc6
openprd-learning-review is a skill published in the GitHub repository DavidLam-oss/obsidian-wechat-converter (307 stars, last pushed yesterday), licensed MIT. It adds 39 tokens to every session and 840 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 2026-09-04.
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