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 szsip239/teamclaw --skill vane-searchgit clone --depth 1 https://github.com/szsip239/teamclawWrote 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/szsip239/teamclaw/vane-search)<a href="https://agentmods.dev/skills/szsip239/teamclaw/vane-search"><img src="https://agentmods.dev/badge/skills/szsip239/teamclaw/vane-search/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/szsip239/teamclaw/vane-search"><img src="https://agentmods.dev/badge/skills/szsip239/teamclaw/vane-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 19 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 111 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00083 | $0.01617 |
| Opus 5 | $0.00042 | $0.00809 |
| Sonnet 5 | $0.00017 | $0.00323 |
| Haiku 4.5 | $0.00008 | $0.00162 |
Grade A, and why
vane-search scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s -X POST "http://localhost:3010/api/search" \ How it starts
The opening of the file, as written. The whole thing — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Vane Search API
本地部署的 Vane (Perplexica) AI 搜索引擎，通过 SearxNG 搜索 + Embedding 重排序 + LLM 总结，返回带引用来源的深度回答。
服务地址
- API:
http://localhost:3010/api/search(POST) - Web UI:
http://localhost:3010 - 容器名:
vane
快速调用
curl -s -X POST "http://localhost:3010/api/search" \
-H "Content-Type: application/json" \
-d '{
"query": "你的搜索问题",
"sources": ["web"],
"chatModel": {
"providerId": "00a2a3e5-5949-4938-9842-037ffa97a47a",
"key": "qwen3.5-plus"
},
"embeddingModel": {
"providerId": "2e10b45d-b8aa-4dfd-8124-c11f86abcba8",
"key": "text-embedding-v3"
}
}'
完整参数说明
| 参数 | 类型 | 必填 | 默认值 | 说明 |
|---|---|---|---|---|
query |
string | ✅ | — | 搜索/提问内容 |
sources |
string[] | ✅ | — | 搜索来源，见下方来源列表 |
chatModel |
object | ✅ | — | {providerId, key} 聊天模型 |
embeddingModel |
object | ✅ | — | {providerId, key} 向量模型 |
optimizationMode |
string | ❌ | "speed" |
搜索深度：speed / balanced / quality |
stream |
boolean | ❌ | false |
是否流式输出 |
history |
array | ❌ | [] |
对话历史，用于多轮追问 |
systemInstructions |
string | ❌ | "" |
自定义系统指令，控制回答风格 |
followUp |
boolean | ❌ | false |
追问模式 |
模型配置
Chat Model (必填)
当前配置为通义千问 (DashScope OpenAI-compatible API)：
{
"providerId": "00a2a3e5-5949-4938-9842-037ffa97a47a",
"key": "qwen3.5-plus"
}
Embedding Model (必填)
当前配置为 DashScope text-embedding-v3 (中文向量模型)：
{
"providerId": "2e10b45d-b8aa-4dfd-8124-c11f86abcba8",
"key": "text-embedding-v3"
}
sources 搜索来源
| 值 | 说明 |
|---|---|
"web" |
网页搜索（通用，最常用） |
"academic" |
学术论文搜索 |
"reddit" |
Reddit 讨论搜索 |
可组合使用：["web", "academic"]
optimizationMode 搜索深度
| 模式 | 说明 | 适用场景 |
|---|---|---|
"speed" |
快速模式，搜索少量来源，直接生成回答 | 简单事实查询、快速确认 |
"balanced" |
均衡模式，搜索更多来源，回答更详细 | 一般调研、信息收集 |
"quality" |
深度模式，多轮推理搜索，最全面最慢 | 深度调研、竞品分析、技术选型 |
返回格式
{
"message": "AI 生成的 Markdown 格式回答（含 [N] 引用标记）",
"sources": [
{
"title": "来源标题",
"url": "来源URL",
"content": "来源摘要内容"
}
]
}
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 · 169 lines · 83 tokens per session scan A 95f6be585bd3
vane-search is a skill published in the GitHub repository szsip239/teamclaw (112 stars, last pushed 22d ago), licensed MIT. It adds 83 tokens to every session and 1,617 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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