Getting it into your agent
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
Wrote 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/blessonism/openclaw-skills/search-layer)<a href="https://agentmods.dev/skills/blessonism/openclaw-skills/search-layer"><img src="https://agentmods.dev/badge/skills/blessonism/openclaw-skills/search-layer/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/blessonism/openclaw-skills/search-layer"><img src="https://agentmods.dev/badge/skills/blessonism/openclaw-skills/search-layer.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 | $0.00116 | $0.03230 |
| Opus 5 | $0.00058 | $0.01615 |
| Sonnet 5 | $0.00023 | $0.00646 |
| Haiku 4.5 | $0.00012 | $0.00323 |
Grade A, and why
search-layer 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.
How it starts
The opening of the file, as written. The whole thing — 297 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Search Layer v2.2 — 意图感知多源检索协议
四源同级：Brave (web_search) + Exa + Tavily + Grok。按意图自动选策略、调权重、做合成。
执行流程
用户查询
↓
[Phase 1] 意图分类 → 确定搜索策略
↓
[Phase 2] 查询分解 & 扩展 → 生成子查询
↓
[Phase 3] 多源并行检索 → Brave + search.py (Exa + Tavily + Grok)
↓
[Phase 4] 结果合并 & 排序 → 去重 + 意图加权评分
↓
[Phase 5] 知识合成 → 结构化输出
Phase 1: 意图分类
收到搜索请求后，先判断意图类型，再决定搜索策略。不要问用户用哪种模式。
| 意图 | 识别信号 | Mode | Freshness | 权重偏向 |
|---|---|---|---|---|
| Factual | "什么是 X"、"X 的定义"、"What is X" | answer | — | 权威 0.5 |
| Status | "X 最新进展"、"X 现状"、"latest X" | deep | pw/pm | 新鲜度 0.5 |
| Comparison | "X vs Y"、"X 和 Y 区别" | deep | py | 关键词 0.4 + 权威 0.4 |
| Tutorial | "怎么做 X"、"X 教程"、"how to X" | answer | py | 权威 0.5 |
| Exploratory | "深入了解 X"、"X 生态"、"about X" | deep | — | 权威 0.5 |
| News | "X 新闻"、"本周 X"、"X this week" | deep | pd/pw | 新鲜度 0.6 |
| Resource | "X 官网"、"X GitHub"、"X 文档" | fast | — | 关键词 0.5 |
详细分类指南见
references/intent-guide.md
判断规则：
- 扫描查询中的信号词
- 多个类型匹配时选最具体的
- 无法判断时默认
exploratory
Phase 2: 查询分解 & 扩展
根据意图类型，将用户查询扩展为一组子查询：
通用规则
- 技术同义词自动扩展：k8s→Kubernetes, JS→JavaScript, Go→Golang, Postgres→PostgreSQL
- 中文技术查询：同时生成英文变体（如 "Rust 异步编程" → 额外搜 "Rust async programming"）
按意图扩展
| 意图 | 扩展策略 | 示例 |
|---|---|---|
| Factual | 加 "definition"、"explained" | "WebTransport" → "WebTransport", "WebTransport explained overview" |
| Status | 加年份、"latest"、"update" | "Deno 进展" → "Deno 2.0 latest 2026", "Deno update release" |
| Comparison | 拆成 3 个子查询 | "Bun vs Deno" → "Bun vs Deno", "Bun advantages", "Deno advantages" |
| Tutorial | 加 "tutorial"、"guide"、"step by step" | "Rust CLI" → "Rust CLI tutorial", "Rust CLI guide step by step" |
| Exploratory | 拆成 2-3 个角度 | "RISC-V" → "RISC-V overview", "RISC-V ecosystem", "RISC-V use cases" |
| News | 加 "news"、"announcement"、日期 | "AI 新闻" → "AI news this week 2026", "AI announcement latest" |
| Resource | 加具体资源类型 | "Anthropic MCP" → "Anthropic MCP official documentation" |
What ships with it
6 files 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.
- 9d ago First seen · 297 lines · 116 tokens per session scan A 9cb421045fce
search-layer is a skill published in the GitHub repository blessonism/openclaw-skills (55 stars, last pushed 5mo ago), licensed MIT. It adds 116 tokens to every session and 3,230 once invoked, about $0.0006 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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