Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/raja21068/AutoResearchnpx agentmods add skills/raja21068/autoresearch/exa-searchWrote 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/raja21068/autoresearch/exa-search)<a href="https://agentmods.dev/skills/raja21068/autoresearch/exa-search"><img src="https://agentmods.dev/badge/skills/raja21068/autoresearch/exa-search/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/raja21068/autoresearch/exa-search"><img src="https://agentmods.dev/badge/skills/raja21068/autoresearch/exa-search.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 | $0.00049 | $0.01896 |
| Opus 5 | $0.00024 | $0.00948 |
| Sonnet 5 | $0.00010 | $0.00379 |
| Haiku 4.5 | $0.00005 | $0.00190 |
Grade A, and why
exa-search 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 7d 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 — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Exa AI-Powered Web Search
Search query: $ARGUMENTS
Role & Positioning
Exa is the broad web search source with built-in content extraction:
| Skill | Best for |
|---|---|
/arxiv |
Direct preprint search and PDF download |
/semantic-scholar |
Published venue papers (IEEE, ACM, Springer), citation counts |
/deepxiv |
Layered reading: search, brief, section map, section reads |
/exa-search |
Broad 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
- FETCH_SCRIPT —
tools/exa_search.pyrelative to the current project. - 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-similarmode) - similar: If present, use
find-similarmode 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
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.
- 7d ago First seen · 184 lines · 49 tokens per session scan A 341c87646a96
exa-search is a skill published in the GitHub repository raja21068/AutoResearch (2 stars, last pushed 3mo ago), licensed MIT. It adds 49 tokens to every session and 1,896 once invoked, about $0.0002 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 2026-09-03.
Other skills, from other repositories
content-refinement-agent
Step 5 of the PaperOrchestra pipeline (arXiv:2604.05018). Iteratively refine drafts/paper.tex by simulating peer review and applying targeted revisions, with strict accept/revert halt rules, deterministic 0-100 decision bands (Accept/Minor/Major/Reject) that drive a target-met early stop, and a Devil's Advocate…
literature-review-agent
Step 3 of the PaperOrchestra pipeline (arXiv:2604.05018). Execute the literature search strategy from outline.json — discover candidate papers via web search, verify them through Semantic Scholar (Levenshtein > 70 fuzzy title match, temporal cutoff, dedup by paperId), cross-corroborate against Crossref + OpenAlex to…
agent-research-aggregator
Pre-pipeline aggregator that scans AI agent cache directories (.claude, .cursor, .antigravity, .openclaw) or any user-specified directory for experimentation logs, extracts insights and numeric results, and formats them as PaperOrchestra-ready inputs (idea.md + experimentallog.md). TRIGGER when the user says…
paper-orchestra
Orchestrate the full PaperOrchestra (Song et al., 2026, arXiv:2604.05018) five-agent pipeline to turn unstructured research materials (idea, experimental log, LaTeX template, conference guidelines, optional figures) into a submission-ready LaTeX manuscript and compiled PDF. TRIGGER when the user asks to "write a paper…
section-writing-agent
Step 4 of the PaperOrchestra pipeline (arXiv:2604.05018). ONE single multimodal LLM call that drafts the remaining paper sections (Abstract, Methodology, Experiments, Conclusion), extracts numeric values from experimentallog.md into LaTeX booktabs tables, splices the generated figures from Step 2, and merges…
plotting-agent
Step 2 of the PaperOrchestra pipeline (arXiv:2604.05018). Execute the visualization plan from outline.json — render plots and conceptual diagrams from experimentallog.md and idea.md, optionally refine via VLM critique loop, and produce context-aware captions. Runs in parallel with the literature-review-agent. TRIGGER…