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 BingHanOfUESTC/open_agent_team --skill output-evaluation-rubricgit clone --depth 1 https://github.com/BingHanOfUESTC/open_agent_teamWrote 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/binghanofuestc/open_agent_team/output-evaluation-rubric)<a href="https://agentmods.dev/skills/binghanofuestc/open_agent_team/output-evaluation-rubric"><img src="https://agentmods.dev/badge/skills/binghanofuestc/open_agent_team/output-evaluation-rubric/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/binghanofuestc/open_agent_team/output-evaluation-rubric"><img src="https://agentmods.dev/badge/skills/binghanofuestc/open_agent_team/output-evaluation-rubric.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 | $0.00028 | $0.00402 |
| Opus 5 | $0.00014 | $0.00201 |
| Sonnet 5 | $0.00006 | $0.00080 |
| Haiku 4.5 | $0.00003 | $0.00040 |
Grade A, and why
output-evaluation-rubric 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 9d 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
Output Evaluation Rubric
评价的目标是判断结果是否达到 Boss 期望，而不是鼓励模型复制参考输出。
1. 评价维度
默认维度：
任务完成度
期望输出匹配度
结构完整度
事实或逻辑可靠性
可读性
风格适配
可复用技能贡献度
污染风险控制
Boss 给出特定评价标准时，优先使用 Boss 标准，同时保留污染风险控制。
2. P0 / P1 / P2
P0：不改不能通过，例如任务没完成、结构错误、污染风险高、核心事实错。
P1：明显影响质量，例如表达不稳、结构缺口、部分标准未满足。
P2：可优化项，例如局部措辞、细节丰富度、次要格式。
3. 失败归因
每个失败项必须归因：
skill 缺口：当前 skills 没有提供必要方法。
skill 污染：skills 过拟合参考输出或任务专属信息。
执行偏差：skills 足够，但执行时没有遵守。
输入不足：Boss 信息不足，无法可靠完成。
评价冲突：Boss 标准之间存在冲突。
4. 评分要求
必须给分项分
必须给综合分
必须解释扣分原因
必须给下一轮动作建议
不得只说“接近预期”
不得因文本相似而忽略泛化性
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.
- 9d ago First seen · 68 lines · 28 tokens per session scan A 9ff32c1e70b4
output-evaluation-rubric is a skill published in the GitHub repository BingHanOfUESTC/open_agent_team (106 stars, last pushed 2mo ago), licensed MIT. It adds 28 tokens to every session and 402 once invoked, about $0.0001 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.
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