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-experience-diagnostic-candidate-eval-20260617123229git 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-experience-diagnostic-candidate-eval-20260617123229)<a href="https://agentmods.dev/skills/mileson/openprd/openprd-experience-diagnostic-candidate-eval-20260617123229"><img src="https://agentmods.dev/badge/skills/mileson/openprd/openprd-experience-diagnostic-candidate-eval-20260617123229/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/mileson/openprd/openprd-experience-diagnostic-candidate-eval-20260617123229"><img src="https://agentmods.dev/badge/skills/mileson/openprd/openprd-experience-diagnostic-candidate-eval-20260617123229.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 | $0.00037 | $0.00911 |
| Opus 5 | $0.00018 | $0.00456 |
| Sonnet 5 | $0.00007 | $0.00182 |
| Haiku 4.5 | $0.00004 | $0.00091 |
Grade A, and why
openprd-experience-diagnostic-candidate-eval-20260617123229 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.
This is a copy
86% identical to openprd-experience-diagnostic-candidate-eval-20260612183730 — 22 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
openprd-experience-diagnostic-candidate-eval-20260617123229
状态：draft 候选目录：
.openprd/knowledge/candidates/candidate-eval-20260617123229Promote：openprd quality . --learn --from .openprd/knowledge/candidates/candidate-eval-20260617123229
触发条件
- 本轮结果里已经出现可复用的症状、排查线索或根因模式，不应该只留在当前对话里。
- 这次改动直接影响 Agent / harness / hook / skill 行为，后续很容易再次踩到同类判断问题。
- 这次修复已经带有验证或收尾证据，适合尽快抽象成项目级研发经验。
- dev-check
- doctor-green
- run-verify
- quality-verify
- 只回复 ok
适用范围
- 抽象模式: 同类故障通常会先在 runtime-events、timeline、root-cause-candidates 和 diagnostic-report 中留下证据。只要实现阶段就把这些结构化诊断面铺好，后续多数问题都能先靠现有证据定位，而不是临时补日志。
- 适用于项目源码或核心流程已经落地、需要把实现经验固化为项目知识的任务。
- 适用于本轮补过验证或测试夹具，后续同类需求需要同步复用验证方式的任务。
- 特别适用于 Agent、hook、harness、quality 或 growth 工作流改动，避免下次再次靠聊天上下文兜底。
典型输入
- 任务场景: dev-check
- 相关文件: src/visual-compare.js、src/quality-visual-review.js、src/agent-integration.js、src/codex-hook-runner-template.mjs、src/test-strategy.js、src/quality.js
- 已有证据类型: diagnostic-report
- 验证信号: dev-check、quality-verify
典型输出
- 项目经验候选与诊断包
- 待确认的项目经验草案
- 验证结论: dev-check attention=1, warning=5
- 可复用的验证链路与收尾动作
下次触发时先看什么
src/visual-compare.jssrc/quality-visual-review.jssrc/agent-integration.jssrc/codex-hook-runner-template.mjssrc/test-strategy.jssrc/quality.jstest/openprd-quality-standards.test.jstest/openprd-agent-integration.test.js.openprd/harness/turn-state.json
不要直接套用
- 如果只是文件名、路径或个别词相似，但当前目标和验证方式不同，不要直接套用。
- 如果当前问题没有出现相似症状、事件或证据入口，不要因为改到相似模块就直接照搬旧结论。
- 如果本轮已经有更新的现场证据，先核对新证据，再决定是否复用旧经验。
可复用模式
- 先按本轮诊断线索复走一次，再补最小必要证据。
验证方式
- dev-check attention=1, warning=5
- quality production-ready
- 复现一次同类路径，确认新的诊断包仍能导出 runtime-events、timeline、root-cause-candidates 和 diagnostic-report。
- 重点核对 dev-check -> doctor-green -> run-verify 的顺序是否符合预期。
- 修复后再次执行同一路径，确认时间线不再在历史失败断点中断。
- 把最终诊断包与质量报告一起归档，确保后续 Agent 能直接复用已有排查路径。
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.
- 12d ago First seen · 75 lines · 37 tokens per session scan A 725c14f6e260
openprd-experience-diagnostic-candidate-eval-20260617123229 is a skill published in the GitHub repository mileson/openprd (50 stars, last pushed 3d ago), licensed MIT. It adds 37 tokens to every session and 911 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to openprd-experience-diagnostic-candidate-eval-20260612183730, differing in 22 lines, and is treated as a copy.
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