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feat: add SearXNG as a native web search backend
Adds SearXNG (https://docs.searxng.org) as a self-hosted, privacy-first web search backend alongside Firecrawl, Tavily, Exa, and Parallel. SearXNG is a meta-search engine that aggregates results from 70+ search engines. No API key needed -- just set SEARXNG_URL to your instance. Changes: - tools/web_tools.py: _get_searxng_url(), _searxng_search(), search dispatch, extract falls back to Firecrawl (SearXNG is search-only) - hermes_cli/tools_config.py: SearXNG provider in web tool picker - hermes_cli/config.py: SEARXNG_URL env var, diagnostics, set command - tests/tools/test_web_tools_searxng.py: 15 tests - optional-skills/research/searxng-search/: agent-guided skill - Docs: configuration.md, environment-variables.md, skills catalogs Based on #6071 by @gnanam1990, #8106 by @cro, #2572 by @bhovig, #2710 and #9961 by @StreamOfRon, #7258 by @coldxiangyu163
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@ -128,6 +128,7 @@ The largest optional category — covers the full ML pipeline from data curation
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| **bioinformatics** | Gateway to 400+ bioinformatics skills from bioSkills and ClawBio. Covers genomics, transcriptomics, single-cell, variant calling, pharmacogenomics, metagenomics, and structural biology. |
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| **domain-intel** | Passive domain reconnaissance using Python stdlib. Subdomain discovery, SSL certificate inspection, WHOIS lookups, DNS records, and bulk multi-domain analysis. No API keys required. |
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| **duckduckgo-search** | Free web search via DuckDuckGo — text, news, images, videos. No API key needed. |
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| **searxng-search** | Free meta-search via SearXNG — aggregates results from 70+ search engines. Self-hosted or use a public instance. No API key needed. |
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| **gitnexus-explorer** | Index a codebase with GitNexus and serve an interactive knowledge graph via web UI and Cloudflare tunnel. |
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| **parallel-cli** | Vendor skill for Parallel CLI — agent-native web search, extraction, deep research, enrichment, and monitoring. |
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| **qmd** | Search personal knowledge bases, notes, docs, and meeting transcripts locally using qmd — a hybrid retrieval engine with BM25, vector search, and LLM reranking. |
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