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-audio-evidencegit 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-audio-evidence)<a href="https://agentmods.dev/skills/mileson/openprd/openprd-audio-evidence"><img src="https://agentmods.dev/badge/skills/mileson/openprd/openprd-audio-evidence.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 | $0.00114 | $0.01767 |
| Opus 5 | $0.00057 | $0.00883 |
| Sonnet 5 | $0.00023 | $0.00353 |
| Haiku 4.5 | $0.00011 | $0.00177 |
Grade A, and why
openprd-audio-evidence 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 — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenPrd Audio Evidence
目标
把“代码改了”“参数看起来合理”升级为可复核的媒体证据闭环：锁定真实来源，独立采集修改前基线，让假设指向具体证据，再从最终输出重新提取并用同一口径复测。
本 skill 不绑定某个音频工具、ASR 引擎或产品。项目自己的目标阈值、引擎约束和业务例外放在项目知识层，不能复制为另一套通用流程。
何时使用
满足任一条件时使用：
- 分析或改变真实音频、视频音轨、录音、混音、静音、消音、哔声、自动剪辑或媒体导出。
- 声称响度、峰值、削波、噪声、连续性、可懂度、声道或同步质量发生变化。
- 评估 ASR、语音识别、转写、说话人、语言、分段、时间戳或语音派生字幕。
- 验证字幕已经正确写入最终媒体，或字幕与最终音轨保持同步。
以下任务默认不进入媒体证据链：纯文案改写、人工翻译、错别字修正，以及只改字幕字体、颜色、字号、布局或其他 UI 样式。编辑器预览截图只证明视觉效果；只有检查已经导出、烧录或作为交付物绑定的字幕与媒体时，才进入 rendered-subtitles。若标题同时提到“字幕”与 UI，不要仅凭关键词触发；按 routing-and-waivers.md 判断真实声明边界。
工作流
1. 定义声明
先把任务声明归入一个或多个范围：acoustic-quality、audio-edit、mix-export、transcription-accuracy、transcription-timing、rendered-subtitles。每个声明都要写明对象、时间范围、预期方向和仍未知的部分，并在 claimResults 单独记录状态与证据引用。一个包包含多个声明时，全局状态按最弱的适用声明收口；只有全部适用声明均有可裁决的 pass 结果，才可写成 comparison-complete。
不要把“算法已接入”写成“音频已改善”，也不要把“字幕文件正确”写成“最终视频字幕正确”。
2. 锁定来源
记录来源路径、来源说明、媒体摘要、时长、目标音轨、时间基准和隐私状态。无法取得的字段显式写为 null，并在 unknownClaims 说明影响；不要用 0 代替未知值。
先确认输入与用户问题确实是同一份媒体。多人声、敏感谈话或可能含个人信息时，只保留完成验证所需的最小材料，并对报告中的文字与路径做脱敏。
3. 独立采集修改前基线
在改参数或改代码前完成基线。只选择能裁决当前声明的指标、片段和人工审听项，不为“指标齐全”堆无关数据：
- 声学、剪辑与混音任务读取 acoustic-analysis.md。
- ASR、字幕时间轴与最终渲染任务读取 transcription-and-subtitle-evaluation.md。
基线必须保存原始测量产物或可复现配置。没有人工金标准时，可以验证结构、覆盖和时间关系，但不得声称转写准确率已经提升。
4. 建立证据关联的假设
每条优化假设至少记录：证据片段、可能根因、替代解释、预测影响和回退路径。优先改动能被前后复测裁决的最小环节。
源码、配置和单元测试可以证明实现合同，不能单独证明真实媒体结果。模拟器、设备、后端和生产环境证据也要分开陈述。
5. 生成最终输出并重新测量
实现后从最终交付媒体重新提取目标音轨、字幕或时间轴，不复用修改前缓存，也不只测中间文件。使用与基线相同的选轨、时间基准、采样窗口、归一化、工具版本和计算口径。若测量口径必须改变，先用新口径重跑基线；无法重跑时记录 settingsChangeReason，但状态不能写成 comparison-complete。
对照至少覆盖：目标指标是否按预测变化、非目标区域是否回归、边界片段是否出现新问题、最终文件摘要是否与被审查文件一致。
6. 收口声明
用 openprd.media-evidence.v1 记录证据包。media-evidence.schema.json 是字段、状态和完成条件的规范源；evidence-bundle-contract.md 只解释如何填，不另行定义第二套合同。状态只能按证据写成：
What ships with it
7 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.
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 · 81 lines · 114 tokens per session scan A 7a3e34d8c6c1
openprd-audio-evidence is a skill published in the GitHub repository mileson/openprd (50 stars, last pushed 9d ago), licensed MIT. It adds 114 tokens to every session and 1,767 once invoked, about $0.0006 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-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-onboard
Guided onboarding for OpenSpec - walk through a complete workflow cycle with narration and real codebase work.
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.