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 AgenticAIPlan/AgenticAISkills --skill data-resource-evaluationgit clone --depth 1 https://github.com/AgenticAIPlan/AgenticAISkillsWrote 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/agenticaiplan/agenticaiskills/data-resource-evaluation)<a href="https://agentmods.dev/skills/agenticaiplan/agenticaiskills/data-resource-evaluation"><img src="https://agentmods.dev/badge/skills/agenticaiplan/agenticaiskills/data-resource-evaluation.svg" alt="Measured on agentmods" 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 | $0.00093 | $0.03937 |
| Opus 5 | $0.00046 | $0.01969 |
| Sonnet 5 | $0.00019 | $0.00787 |
| Haiku 4.5 | $0.00009 | $0.00394 |
Grade A, and why
data-resource-evaluation 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.
How it starts
The opening of the file, as written. The whole thing — 463 lines — stays where its author put it; the contents beside it link to each section on GitHub.
数据资源评估
概述
此 skill 用于管理外部伙伴数据资源的评估流程。将数据资源按类型(资源置换/数商线索)提交给对应负责人,同步记录到知识库文档,并设置定时跟进提醒。
⚠️ 前置检查(Fail-Fast 规则)
重要:在执行任何写操作之前,必须检查配置是否有效!
配置检查规则
在执行第三步(发送评估消息)、第四步(同步更新知识库)、第五步(设置定时提醒)之前,必须验证以下配置:
-
负责人配置检查:
responsible_persons.resource_exchange.account不能是占位符(如 "负责人账号"、"uuapName" 等)responsible_persons.data_vendor_leads.account不能是占位符
-
知识库配置检查:
knowledge_base.doc_url不能是占位符(如 "知识库文档链接")knowledge_base.kb_id不能是占位符(如 "知识库 ID")knowledge_base.doc_id不能是占位符(如 "文档 ID")
检查失败处理
如果检测到配置仍为占位符:
- 立即停止:不执行任何写操作
- 提示用户:明确告知哪些配置项未设置
- 提供指引:指导用户如何修改配置
示例提示
❌ 无法执行评估提交:配置未完成
以下配置项仍为占位符,请先修改 SKILL.md 中的配置:
- responsible_persons.resource_exchange.account: 当前值为 "负责人账号(如流 uuapName)"
- knowledge_base.doc_url: 当前值为 "知识库文档链接"
请修改 ~/.openclaw/skills/data-resource-evaluation/SKILL.md 中的元数据配置后重试。
核心流程
┌─────────────────┐
│ 接收评估请求 │
└────────┬────────┘
▼
┌─────────────────┐
│ 判断评估类型 │
│ 资源置换/数商 │
└────────┬────────┘
▼
┌─────────────────┐
│ 收集数据信息 │
│ 使用标准模板 │
└────────┬────────┘
▼
┌─────────────────┐
│ 发送评估消息 │
│ 给对应负责人 │
└────────┬────────┘
▼
┌─────────────────┐
│ 同步更新知识库 │
│ 追加评估记录 │
└────────┬────────┘
▼
┌─────────────────┐
│ 确认定时提醒 │
│ 每周五跟进 │
└─────────────────┘
触发条件说明
重要:此 skill 仅在用户明确要求执行评估提交/记录/发起动作时触发!
✅ 应该触发的场景
用户表达明确的执行意图,例如:
- "提交评估"
- "帮我记录这个评估"
- "发起一个数据资源评估"
- "登记这个数据资源"
- "把这个数据提交给负责人评估"
- "需要走评估流程"
❌ 不应触发的场景
用户仅进行一般性讨论或咨询,例如:
- "什么是数据资源评估?"
- "数据采购流程是怎样的?"
- "资源置换需要注意什么?"
- "帮我分析一下这个数据的价值"(纯分析,不涉及提交)
判断原则
- 执行意图 vs 讨论意图:只有当用户希望执行具体操作(发送消息、更新文档、创建提醒)时才触发
- 有副作用 vs 无副作用:此 skill 会产生写操作,确保用户已知晓并同意
- 明确指令 vs 模糊提及:用户应明确表达"提交/记录/发起"等动作词汇
第一步:判断评估类型
根据用户意图判断数据资源的评估类型:
资源置换(生态合作)
触发词:资源置换、生态合作、生态资源置换、合作评估、数据交换
适用场景:合作伙伴希望通过数据交换、生态合作方式获取资源,不涉及现金采购
配置项:负责人信息通过 responsible_persons.resource_exchange 配置
数商数据线索(采购)
触发词:数据采购、数商线索、采购评估、线索提交、现金采购
What ships with it
1 file 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.
- 6d ago First seen · 463 lines · 93 tokens per session scan A fe1a4efb2aa8
data-resource-evaluation is a skill published in the GitHub repository AgenticAIPlan/AgenticAISkills (11 stars, last pushed 3mo ago), licensed MIT. It adds 93 tokens to every session and 3,937 once invoked, about $0.0005 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 2026-08-30.
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