CtrlK
BlogDocsLog inGet started
Tessl Logo

exa-search

AI-powered web search via Exa with content extraction. Use when user says "exa search", "web search with content", "find similar pages", or needs broad web results beyond academic databases (arXiv, Semantic Scholar).

54

Quality

62%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Advisory

Suggest reviewing before use

Optimize this skill with Tessl

npx tessl skill review --optimize ./skills/exa-search/SKILL.md
SKILL.md
Quality
Evals
Security

Exa AI-Powered Web Search

Search query: $ARGUMENTS

Role & Positioning

Exa is the broad web search source with built-in content extraction:

SkillBest for
/arxivDirect preprint search and PDF download
/semantic-scholarPublished venue papers (IEEE, ACM, Springer), citation counts
/deepxivLayered reading: search, brief, section map, section reads
/exa-searchBroad web search: blogs, docs, news, companies, research papers — with content extraction

Use Exa when you need results beyond academic databases, or when you want content (highlights, full text, summaries) extracted alongside search results.

Constants

  • EXA_FETCHER — canonical name exa_search.py, resolved per shared-references/integration-contract.md §2 (Policy D1 — standalone /exa-search has no documented fallback, so unresolved helper terminates with an explicit error).
  • MAX_RESULTS = 10 — Default number of results to return.

Overrides (append to arguments):

  • /exa-search "RAG pipelines" — max: 5 — top 5 results
  • /exa-search "diffusion models" — category: research paper — research papers only
  • /exa-search "startup funding" — category: news, start date: 2025-01-01 — recent news
  • /exa-search "transformer" — content: text, max chars: 8000 — full text mode
  • /exa-search "transformer" — content: summary — LLM-generated summaries
  • /exa-search "transformer" — domains: arxiv.org,huggingface.co — domain filter
  • /exa-search "https://arxiv.org/abs/2301.07041" — similar — find similar pages

Setup

Exa requires the exa-py SDK and an API key:

pip install exa-py

Set your API key:

export EXA_API_KEY=your-key-here

Get a key from exa.ai.

Workflow

Step 1: Parse Arguments

Parse $ARGUMENTS for:

  • query: The search query (required) or a URL (for find-similar mode)
  • similar: If present, use find-similar mode instead of search
  • max: Override MAX_RESULTS
  • category: research paper, news, company, personal site, financial report, people
  • content: highlights (default), text, summary, none
  • max chars: Max characters for content extraction
  • type: Search type — auto (default), neural, fast, instant
  • domains: Comma-separated include domains
  • exclude domains: Comma-separated exclude domains
  • include text: Phrase that must appear in results
  • exclude text: Phrase to exclude from results
  • start date: ISO 8601 date — only results after this
  • end date: ISO 8601 date — only results before this
  • location: Two-letter ISO country code

Step 2: Locate Script

Resolve $EXA_FETCHER via the canonical strict-safe chain (see shared-references/integration-contract.md §2). Policy D1 cascade: there is no native inline fallback for Exa (retrieval requires the exa-py SDK + API key, which lives in the fetcher), so unresolved helper means the SKILL cannot produce its primary output — fail with explicit remediation.

cd "$(git rev-parse --show-toplevel 2>/dev/null || pwd)" || exit 1
if [ -z "${ARIS_REPO:-}" ] && [ -f .aris/installed-skills.txt ]; then
    ARIS_REPO=$(awk -F'\t' '$1=="repo_root"{print $2; exit}' .aris/installed-skills.txt 2>/dev/null) || true
fi
EXA_FETCHER=".aris/tools/exa_search.py"
[ -f "$EXA_FETCHER" ] || EXA_FETCHER="tools/exa_search.py"
[ -f "$EXA_FETCHER" ] || { [ -n "${ARIS_REPO:-}" ] && EXA_FETCHER="$ARIS_REPO/tools/exa_search.py"; }
[ -f "$EXA_FETCHER" ] || {
  echo "ERROR: exa_search.py not resolved at .aris/tools/, tools/, or \$ARIS_REPO/tools/." >&2
  echo "       Fix: rerun bash tools/install_aris.sh, export ARIS_REPO, or copy the helper to tools/." >&2
  echo "       Also ensure 'exa-py' is installed: pip install exa-py" >&2
  exit 1
}

Step 3: Execute Search

Standard search:

python3 "$EXA_FETCHER" search "QUERY" --max 10 --content highlights

With filters:

python3 "$EXA_FETCHER" search "QUERY" --max 10 \
  --category "research paper" \
  --start-date 2025-01-01 \
  --content text --max-chars 8000

Find similar pages:

python3 "$EXA_FETCHER" find-similar "URL" --max 5 --content highlights

Get content for known URLs:

python3 "$EXA_FETCHER" get-contents "URL1" "URL2" --content text

Step 4: Present Results

Format results as a structured table:

| # | Title | Authors | Venue/Publisher | URL | Date | Key Content |
|---|-------|---------|-----------------|-----|------|-------------|

For each result:

  • Show title and URL
  • Show published date if available
  • Show highlights, text excerpt, or summary depending on content mode
  • Flag particularly relevant results
  • For category: "research paper" hits only — also record authors (from Exa's author/authors fields, or fallback: parse from the result snippet) and venue/publisher (from publisher, source, or the domain hosting the paper). These are needed by Step 6's wiki hook; if either is unavailable for a given hit, skip wiki ingest for that one hit and log a note.

Step 5: Offer Follow-up

After presenting results, suggest:

  • Deepen: "I can fetch full text for any of these results"
  • Find similar: "I can find pages similar to any result"
  • Narrow: "I can re-search with domain/date/text filters"

Step 6: Update Research Wiki (if active, research-paper results only)

Required when research-wiki/ exists AND the search returned results of category: "research paper"; skip silently otherwise. General web results (blog posts, docs, news) are not ingested — the wiki is for papers only.

When the predicates hold, resolve $WIKI_SCRIPT per the canonical chain at shared-references/wiki-helper-resolution.md (Variant B — warn-and-skip). For each research paper hit, try to recover an arXiv ID from the URL (arxiv.org/abs/<id>); if present, use --arxiv-id. Otherwise fall back to manual metadata:

if [ -d research-wiki/ ] and query category was "research paper":
    cd "$(git rev-parse --show-toplevel 2>/dev/null || pwd)" || exit 1
    ARIS_REPO="${ARIS_REPO:-$(awk -F'\t' '$1=="repo_root"{print $2; exit}' .aris/installed-skills.txt 2>/dev/null)}"
    WIKI_SCRIPT=".aris/tools/research_wiki.py"
    [ -f "$WIKI_SCRIPT" ] || WIKI_SCRIPT="tools/research_wiki.py"
    [ -f "$WIKI_SCRIPT" ] || { [ -n "${ARIS_REPO:-}" ] && WIKI_SCRIPT="$ARIS_REPO/tools/research_wiki.py"; }
    [ -f "$WIKI_SCRIPT" ] || {
      echo "WARN: research_wiki.py not found; exa-search results delivered, wiki ingest skipped. Fix: bash tools/install_aris.sh, export ARIS_REPO, or cp <ARIS-repo>/tools/research_wiki.py tools/." >&2
      WIKI_SCRIPT=""
    }
    [ -n "$WIKI_SCRIPT" ] && for each research-paper hit in results:
        if URL matches arxiv.org/abs/<id>:
            python3 "$WIKI_SCRIPT" ingest_paper research-wiki/ \
                --arxiv-id "<id>"
        else:
            python3 "$WIKI_SCRIPT" ingest_paper research-wiki/ \
                --title "<title>" --authors "<authors joined by , >" \
                --year <year> --venue "<venue or publisher>"

The helper handles slug / dedup / page / index / log — do not handwrite papers/<slug>.md. See shared-references/integration-contract.md.

Key Rules

  • Always check that EXA_API_KEY is set before searching
  • Default to highlights content mode for a good balance of speed and context
  • Use category: "research paper" when the user is clearly looking for academic content
  • Use text content mode when the user needs full page content
  • Combine with /arxiv or /semantic-scholar for comprehensive literature coverage
Repository
wanshuiyin/Auto-claude-code-research-in-sleep
Last updated
Created

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.