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 sasakiblog26-lgtm/exa-mcp-server --skill company-searchgit clone --depth 1 https://github.com/sasakiblog26-lgtm/exa-mcp-serverWrote 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/sasakiblog26-lgtm/exa-mcp-server/company-search)<a href="https://agentmods.dev/skills/sasakiblog26-lgtm/exa-mcp-server/company-search"><img src="https://agentmods.dev/badge/skills/sasakiblog26-lgtm/exa-mcp-server/company-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/sasakiblog26-lgtm/exa-mcp-server/company-search"><img src="https://agentmods.dev/badge/skills/sasakiblog26-lgtm/exa-mcp-server/company-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 | $0.00047 | $0.00803 |
| Opus 5 | $0.00023 | $0.00402 |
| Sonnet 5 | $0.00009 | $0.00161 |
| Haiku 4.5 | $0.00005 | $0.00080 |
Grade A, and why
company-research 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 12d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- company-research — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Company Research
Tool Restriction (Critical)
ONLY use web_search_advanced_exa. Do NOT use web_search_exa or any other Exa tools.
Token Isolation (Critical)
Never run Exa searches in main context. Always spawn Task agents:
- Agent runs Exa search internally
- Agent processes results using LLM intelligence
- Agent returns only distilled output (compact JSON or brief markdown)
- Main context stays clean regardless of search volume
Dynamic Tuning
No hardcoded numResults. Tune to user intent:
- User says "a few" → 10-20
- User says "comprehensive" → 50-100
- User specifies number → match it
- Ambiguous? Ask: "How many companies would you like?"
Query Variation
Exa returns different results for different phrasings. For coverage:
- Generate 2-3 query variations
- Run in parallel
- Merge and deduplicate
Categories
Use appropriate Exa category depending on what you need:
company→ homepages, rich metadata (headcount, location, funding, revenue)news→ press coverage, announcementspeople→ LinkedIn profiles (public data)- No category (
type: "auto") → general web results, deep dives, broader context
Start with category: "company" for discovery, then use other categories or no category for deeper research.
Category-Specific Filter Restrictions
When using category: "company", these parameters cause 400 errors:
includeDomains/excludeDomainsstartPublishedDate/endPublishedDatestartCrawlDate/endCrawlDate
When searching without a category (or with news), domain and date filters work fine.
Universal restriction: includeText and excludeText only support single-item arrays. Multi-item arrays cause 400 errors across all categories.
Public LinkedIn via Exa: category: "people", no other filters.
Auth-required LinkedIn → use Claude in Chrome browser fallback.
Browser Fallback
Auto-fallback to Claude in Chrome when:
- Exa returns insufficient results
- Content is auth-gated
- Dynamic pages need JavaScript
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.
- 12d ago First seen · 116 lines · 47 tokens per session scan A 225a7d00d1ce
company-research is a skill published in the GitHub repository sasakiblog26-lgtm/exa-mcp-server (1 stars, last pushed 5mo ago), licensed MIT. It adds 47 tokens to every session and 803 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 2026-08-31.
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