Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add tdimino/claude-code-minoan --skill exa-searchgit clone --depth 1 https://github.com/tdimino/claude-code-minoanWrote 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/tdimino/claude-code-minoan/exa-search)<a href="https://agentmods.dev/skills/tdimino/claude-code-minoan/exa-search"><img src="https://agentmods.dev/badge/skills/tdimino/claude-code-minoan/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/tdimino/claude-code-minoan/exa-search"><img src="https://agentmods.dev/badge/skills/tdimino/claude-code-minoan/exa-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00080 | $0.02572 |
| Opus 5 | $0.00040 | $0.01286 |
| Sonnet 5 | $0.00016 | $0.00514 |
| Haiku 4.5 | $0.00008 | $0.00257 |
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 8d 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 — 242 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Exa Search Skill
5 specialized scripts for Exa AI search API—neural search, content extraction, similar pages, research with citations, and async pro research.
Prerequisite: EXA_API_KEY environment variable. Get key at https://dashboard.exa.ai
Token-Efficient Search
Inspired by Anthropic's dynamic filtering—always filter before reasoning. ~24% fewer tokens, ~11% better accuracy.
The Principle: Search Cheaply → Filter → Extract Selectively → Reason
DO:
# Step 1: Search with --no-text (titles/URLs only — cheapest)
python3 ~/.claude/skills/exa-search/scripts/exa_search.py "query" -n 20 --no-text
# Step 2: Evaluate titles, pick best 3-5 URLs
# Step 3: Extract only those URLs with bounded content
python3 ~/.claude/skills/exa-search/scripts/exa_contents.py URL1 URL2 --highlights --max-chars 3000
DON'T: Search with full text for 50 results, then reason over all of it.
Use API-Level Filters First (Free Filtering)
These reduce results at the API level before you ever see them:
--must-include "term"— results must contain this string--must-exclude "term"— removes irrelevant results--domains site1.com site2.com— restrict to authoritative sources--category "research paper"— eliminate irrelevant content types--after 2025-01-01/--before— temporal filtering
Use Summaries Over Full Text
When you need the gist, not raw content:
# AI-distilled summaries — much smaller than full text
python3 ~/.claude/skills/exa-search/scripts/exa_search.py "query" --summary "Key findings" -n 5
Use Bounded Context for RAG
# Capped context string — prevents unbounded token usage
python3 ~/.claude/skills/exa-search/scripts/exa_search.py "query" --context --context-chars 5000
Post-Process with filter_web_results.py
Pipe Exa JSON output through the Firecrawl filter script for additional reduction:
python3 ~/.claude/skills/exa-search/scripts/exa_search.py "query" --json | \
python3 ~/.claude/skills/firecrawl/scripts/filter_web_results.py \
--fields "title,url,text" --max-chars 3000
What ships with it
9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- codex-agent-guide.md 2.0 KB
- README.md 6.3 KB
- references/exa-scripts-reference.md 14 KB
- scripts/exa_contents.py 16 KB runs code
- scripts/exa_research_async.py 11 KB runs code
- scripts/exa_research.py 15 KB runs code
- scripts/exa_search.py 29 KB runs code
- scripts/exa_similar.py 17 KB runs code
- scripts/test_exa.py 24 KB runs 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.
- 8d ago First seen · 242 lines · 80 tokens per session scan A ca82ec0b1c70
exa-search is a skill published in the GitHub repository tdimino/claude-code-minoan (41 stars, last pushed yesterday), licensed MIT. It adds 80 tokens to every session and 2,572 once invoked, about $0.0004 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.
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