Bilingual search-layer skill for OpenClaw that turns ordinary web lookup into multi-source retrieval, intent-aware ranking, adaptive weighting, thread-pulling research, Chinese-query optimization, and finance-aware realtime prioritization. Use when the user asks for web search, deep research, latest status/news, comparisons, resource finding, Chinese-language search, or realtime market data such as stocks, indices, forex, and crypto prices. Prefer this over raw web_search when you want broade...
Scanned 9/9/2026
Install to Claude Code
npx -y skills add Lord1Egypt/awesome-skill-forge --skill openclaw-glasses --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Openclaw Glasses?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/lord1egypt-openclaw-glasses)More formats (shields.io, HTML) on the badges page.
---
name: openclaw-glasses
description: Bilingual search-layer skill for OpenClaw that turns ordinary web lookup into multi-source retrieval, intent-aware ranking, adaptive weighting, thread-pulling research, Chinese-query optimization, and finance-aware realtime prioritization. Use when the user asks for web search, deep research, latest status/news, comparisons, resource finding, Chinese-language search, or realtime market data such as stocks, indices, forex, and crypto prices. Prefer this over raw web_search when you want broader coverage, better ranking, deeper context, or more reliable realtime quotes.
---
# OpenClaw Glasses
**See wider. Rank smarter. Answer with context.**
OpenClaw Glasses is a search layer for OpenClaw. It starts with ordinary web lookup, then adds multi-source retrieval, intent-aware reranking, adaptive weighting, optional thread-pulling research, Chinese-query optimization, and finance-aware realtime prioritization.
OpenClaw Glasses 是一个给 OpenClaw 用的“搜索层 / 增强检索层”。它不是简单叠加几个搜索源,而是把**多源召回、意图感知排序、权重自适应、链式追踪、中文优化、金融实时优先级**整合成一条完整检索链,让结果更接近“先找对,再排对,最后答对”。
## Public-facing summary
OpenClaw Glasses extends OpenClaw's native web tools into a smarter retrieval stack:
- **multi-source search** for broader recall and lower single-source bias
- **intent-aware search** for factual lookups, status/news, comparisons, tutorials, and exploratory research
- **adaptive weighting** so ranking changes with query type instead of using one fixed recipe
- **thread-pulling / follow-up research** for issues, discussions, and linked references
- **Chinese-query optimization** with CJK-aware matching and source weighting
- **finance-aware realtime prioritization** for stocks, indices, forex, and crypto quotes
OpenClaw Glasses 会把 OpenClaw 原生 web tools 扩展成一条更完整的检索链:
- **多源搜索**:扩大召回面,减少单一来源偏差
- **意图感知检索**:区分事实查询、状态更新、新闻、对比、教程、探索式研究
- **权重自适应**:不同问题走不同排序逻辑,而不是一套固定权重打天下
- **链式追踪 / 深挖**:遇到 issue、讨论帖、引用链时可以继续往下追
- **中文搜索优化**:针对中文查询做 CJK-aware 匹配与中文友好源加权
- **金融实时增强**:对股票、指数、外汇、加密资产等实时价格问题给出更稳的优先级
## Example triggers
- "帮我查一下 OpenClaw 最新进展,并按可靠性排序"
- "Compare Bun vs Deno for production backend use"
- "AAPL 最新股价"
- "BTC 实时价格和 24h 涨跌"
## Quick start
1. Use OpenClaw's built-in `web_search` as the agent-facing source when available.
2. Use `scripts/search.py` to aggregate additional providers and rerank results.
3. For status / exploratory / comparison work, prefer multi-query retrieval and intent scoring.
4. For finance price queries, let the finance-aware path boost Alpha Vantage and Binance results.
## What this skill adds
- Intent-aware search modes: factual, status, comparison, tutorial, exploratory, news, resource
- Multi-source aggregation: Exa, Tavily, Grok, Gemini, Kimi
- Chinese-query optimization:
- CJK-aware keyword matching instead of space-splitting only
- modest boosts for Chinese-friendly sources when the query is in Chinese
- Finance-aware weighting:
- boosts Alpha Vantage for stocks / ETFs / forex / index proxies
- boosts Binance for crypto realtime quotes
- Optional GitHub thread-pulling and reference extraction for deeper research
## Workflow
### 1. Pick the mode by intent
- Factual / tutorial → `answer` or light `deep`
- Status / news / comparison / exploratory → `deep`
- Resource finding → `fast`
- Finance realtime queries → `fast` for direct quote lookups, `deep` when combining quote + broader context
For intent examples and phrasing cues, read `references/intent-guide.md`.
### 2. Run the aggregator
Basic:
```bash
python3 scripts/search.py "query" --mode deep --intent exploratory --num 5
```
Multi-query comparison:
```bash
python3 scripts/search.py \
--queries "Bun vs Deno" "Bun advantages" "Deno advantages" \
--mode deep \
--intent comparison
```
Finance quote:
```bash
python3 scripts/search.py "BTC 实时价格" --mode deep --intent status --source alpha-vantage,binance,gemini,kimi,tavily
```
### 3. Synthesize by topic, not by provider
- Answer first, then cite
- Group by themes or findings
- Call out conflicts explicitly
- Treat single-source or older claims more cautiously
## Scripts
### `scripts/search.py`
Primary multi-source retrieval and reranking entrypoint.
Capabilities:
- intent-aware scoring
- multi-query execution
- provider fusion
- Chinese-query weighting
- finance-aware realtime boosts
- optional extract-refs integration
### `scripts/fetch_thread.py`
Deep-fetch GitHub issues / PRs or generic pages to extract structured references.
### `scripts/chain_tracker.py`
Recursive thread-pulling / follow-up exploration with relevance gating.
### `scripts/relevance_gate.py`
Batch relevance filtering for candidate links.
## References
- `references/intent-guide.md` — intent cues and search-mode guidance
- `references/authority-domains.json` — authority weighting rules
- `references/research-light-regression-samples.md` — research-light behavior examples
## Configuration notes
Do not hardcode secrets in the skill.
Expected runtime configuration:
- search provider keys via environment or a local credentials file
- optional reuse of OpenClaw's existing web-search provider config
- finance sources should remain optional; degrade gracefully if unavailable
## Publishing / safety
Before packaging or publishing:
- remove all plaintext secrets
- remove machine-specific notes, personal paths, and private identifiers
- verify that examples and docs contain no local credentials or private data
- run the validator / packager before publishing
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!