- 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
- Use OpenClaw's built-in
web_searchas the agent-facing source when available. - Use
scripts/search.pyto aggregate additional providers and rerank results. - For status / exploratory / comparison work, prefer multi-query retrieval and intent scoring.
- 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 →
answeror lightdeep - Status / news / comparison / exploratory →
deep - Resource finding →
fast - Finance realtime queries →
fastfor direct quote lookups,deepwhen combining quote + broader context
For intent examples and phrasing cues, read references/intent-guide.md.
2. Run the aggregator
Basic:
python3 scripts/search.py "query" --mode deep --intent exploratory --num 5Multi-query comparison:
python3 scripts/search.py \
--queries "Bun vs Deno" "Bun advantages" "Deno advantages" \
--mode deep \
--intent comparisonFinance quote:
python3 scripts/search.py "BTC 实时价格" --mode deep --intent status --source alpha-vantage,binance,gemini,kimi,tavily3. 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 guidancereferences/authority-domains.json— authority weighting rulesreferences/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