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-router/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-router)<a href="https://agentmods.dev/skills/davidlam-oss/obsidian-wechat-converter/openprd-router"><img src="https://agentmods.dev/badge/skills/davidlam-oss/obsidian-wechat-converter/openprd-router/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-router"><img src="https://agentmods.dev/badge/skills/davidlam-oss/obsidian-wechat-converter/openprd-router.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 | $0.00031 | $0.01496 |
| Opus 5 | $0.00015 | $0.00748 |
| Sonnet 5 | $0.00006 | $0.00299 |
| Haiku 4.5 | $0.00003 | $0.00150 |
Grade A, and why
openprd-router 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 7d 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 — 52 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenPrd Router
把这份 skill 当成 OpenPrd 的入口路由，而不是长文规则仓库。
先做什么
- 先判断 executionMode。Codex automation、Claude Code headless、cron、scheduled、unattended task 这类无人值守自动化默认进入 automation-safe mode：不要运行
openprd run . --context，不要注入 OpenPrd context，不要求openprd dev-check/quality/doctor，按该自动化自己的 runbook、日志、测试和通知合同收口。 - 只有 automation prompt 或环境明确写明“这是 OpenPrd 维护任务”“显式启用 OpenPrd / enable OpenPrd / openprd-maintenance”时，才在自动化里恢复 OpenPrd 工作流。
- 如果用户当前明确在说“帮我梳理下”“先想清楚”“进入脑暴模式”，先读
$openprd-requirement-intake，并优先运行openprd run . --context --message <用户原话>；需要时直接进入openprd brainstorm . --open，不要只跑不带 message 的openprd run . --context。 - 其他互动场景再读
.openprd/当前状态，并把openprd run . --context当作纯读取的建议上下文，而不是自动执行指令；只有 hook/调用方确实要记录本次上下文使用时，才显式加--record-context。 - 如果当前是空白工作区的前端/页面冷启动，而且用户已经给了明确的页面主题、模块范围或“直接实现”的意图，优先改用
openprd run . --context --message <用户原话>；不要先跑不带 message 的openprd run . --context，再被空白工作区自己的clarify-user带偏。 - 需要具体命令时，优先读取
.openprd/harness/command-catalog.md，不要把命令清单继续塞回AGENTS.md。 - 需要共用约束时，读
$openprd-shared；需要主工作流时，读$openprd-harness。 - 任务涉及界面、页面、视觉、样式、信息架构、内容型页面或前端体验时，先读取
$openprd-frontend-design；新界面、结构性 UI 改造、设计系统或 Impeccable handoff 再读取$openprd-ui-context。局部低风险修正使用 UI Context 的local-fix路径。 - 如果这类空白前端任务在带 message 的前提下仍短暂返回
clarify-user，但用户原话已经明确要求直接实现单页/首页/原型，就把它当成摘要级提醒；先用 3 到 5 行 mini-plan 收口，再按 frontend design 的design-starter -> Patch Mode路径继续，不要回到长澄清或模板源码漫游。
路由表
- 需求入口分流、用户可见需求类型与内部 L0/L1/L2 路由码对照、PRD 场景视角选择：
$openprd-requirement-intake - 主工作流、review/change/tasks、
run/loop：$openprd-harness - 前端设计框架、审美资产库、主题/骨架/组件/配方/模板、事实与素材前置门：
$openprd-frontend-design - 项目双路径理解、专业 UI/UX 方向、PRODUCT.md/DESIGN.md 与 Impeccable 交接：
$openprd-ui-context - 测试策略分流、分层验证和任务级 evidence-plan：
$openprd-test-strategy - 最佳实践、benchmark、公开 GitHub 仓库、第三方技术事实、prompt/context engineering：
$openprd-benchmark-router docs/basic/、文件说明书、文件夹 README、文档标准：$openprd-standards- 就绪验证、EVO 门禁、HTML 质量评估报告、项目经验沉淀：
$openprd-quality - 架构图、产品流程图、解释型 SVG、可视化评审、大界面改动效果图方案评审：
$openprd-diagram-review与$openprd-harness - 长时间只读挖掘、参考项目持续调研、requirements/specs/tasks 补全：
$openprd-discovery-loop - 学习包、归档阅读器、知识整理：
$openprd-learning-review
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.
- 7d ago First seen · 52 lines · 31 tokens per session scan A 19a1edbdd5af
openprd-router is a skill published in the GitHub repository DavidLam-oss/obsidian-wechat-converter (310 stars, last pushed yesterday), licensed MIT. It adds 31 tokens to every session and 1,496 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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