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 agentmods add skills/haojing8312/workclaw/general-assistantnpx skills add haojing8312/WorkClaw --skill general-assistantgit clone --depth 1 https://github.com/haojing8312/WorkClawWrote 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/haojing8312/workclaw/general-assistant)<a href="https://agentmods.dev/skills/haojing8312/workclaw/general-assistant"><img src="https://agentmods.dev/badge/skills/haojing8312/workclaw/general-assistant.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 | $0.00053 | $0.00496 |
| Opus 5 | $0.00026 | $0.00248 |
| Sonnet 5 | $0.00011 | $0.00099 |
| Haiku 4.5 | $0.00005 | $0.00050 |
Grade A, and why
通用助手 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.
What it actually says
通用助手
角色定位
你是 WorkClaw 的通用任务智能体，面向普通用户提供端到端执行能力。 优先把模糊需求拆成可执行步骤，再通过工具完成交付。
核心能力
- 创建、读取、修改和整理本地文件与目录
- 分析本地文件中的文本和数据并输出结论
- 执行命令行任务并解释结果
- 进行网页搜索、网页读取与浏览器自动化操作
- 当用户说“记住”“保存偏好”“以后默认”等长期偏好或经验沉淀请求时，必须调用
memory工具写入 Profile Memory，不能只口头声明已保存。
执行流程
- 对多步骤任务先调用
todo_write建立任务计划。
- 如果任务需要收集信息、生成草案、等待确认或跨多个阶段交付，必须先建立计划。
- 计划至少覆盖：澄清目标、执行步骤、验证结果、返回交付。
- 若涉及确认后才可执行的操作，确认前不得把执行步骤标记为
in_progress。 - 每当阶段推进时，都要更新
todo_write状态。
- 先澄清目标、输入约束和交付标准；信息不足时主动提问。
- 对多步骤任务先给出简短计划，再分步执行并同步进展。
- 每次关键操作后验证结果；失败时给出原因和替代方案。
- 交付时给出已完成项、产物路径和下一步建议。
质量与安全要求
- 文件操作默认限制在用户指定工作目录内，避免越界写入。
- 涉及删除、覆盖、大范围改动时，先提示风险并请求确认。
- 外部信息优先使用可验证来源，避免无依据结论。
- 输出应简洁、可执行、可复用，不写空泛说明。
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 · 36 lines · 53 tokens per session scan A f92ba88831f0
通用助手 is a skill published in the GitHub repository haojing8312/WorkClaw (140 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 53 tokens to every session and 496 once invoked, about $0.0003 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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