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 shulan-io/shulan-mcp --skill shulan-mcpgit clone --depth 1 https://github.com/shulan-io/shulan-mcpWrote 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/shulan-io/shulan-mcp/shulan-mcp)<a href="https://agentmods.dev/skills/shulan-io/shulan-mcp/shulan-mcp"><img src="https://agentmods.dev/badge/skills/shulan-io/shulan-mcp/shulan-mcp/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/shulan-io/shulan-mcp/shulan-mcp"><img src="https://agentmods.dev/badge/skills/shulan-io/shulan-mcp/shulan-mcp.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 | $0.00072 | $0.00555 |
| Opus 5 | $0.00036 | $0.00278 |
| Sonnet 5 | $0.00014 | $0.00111 |
| Haiku 4.5 | $0.00007 | $0.00056 |
Grade A, and why
shulan-data 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 11d 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
数懒数据调研（ShuLan Data Research）
使用数懒 AI 数据中台完成商业数据调研，并产出可执行的报告（达人清单、招标汇总、企业洞察、招聘信号、舆情监测）。
前置条件
- 已配置数懒 MCP Server（
shulan-mcp），并在 https://shulan.io 开放平台生成sl_前缀 API Key - 环境变量：
SHULAN_API_KEY、SHULAN_BASE_URL（托管环境为https://shulan.io）
可用工具
shulan_health— 检查服务状态shulan_create_task— 创建数据调研任务（自动扣费，多退少不补）shulan_get_task— 查询任务状态与报告shulan_market— 查询报告市集shulan_get_report— 获取报告详情
工作流
- 澄清需求：确认地域、对象、时间窗口、期望交付物（清单/横评/ROI 模型）。
- 拆解问题：把一句话需求拆成「主题 + 范围 + 指标 + 时间」四要素。
- 创建任务：调用
shulan_create_task，传入 question 与可选 dataSources/cost。 - 轮询结果：调用
shulan_get_task，状态done后获取html_url。 - 解读交付：向用户说明关键结论、置信度与数据来源；提醒 AI 生成内容标识与「多退少不补」结算规则。
注意事项
- 任务按实际成本结算，预估点数仅作参考；提示用户可在网页端查看明细。
- 数据来源以报告内「数据来源核验凭证」为准；演示构造模式会明确标注。
- 不承诺不存在的实时数据能力；涉及平台会员数据时使用聚合分析口径。
Examples
Example usage or prompts
Notes
- Additional notes or caveats
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.
- 11d ago First seen · 46 lines · 72 tokens per session scan A 4e9bb5b6fba6
shulan-data is a skill published in the GitHub repository shulan-io/shulan-mcp (0 stars, last pushed 20d ago), licensed MIT. It adds 72 tokens to every session and 555 once invoked, about $0.0004 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 2026-08-31.
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