company-research

company-research is a skill for Claude Code from exa-labs/agent-skills. It costs 46 tokens per session (1,467 once invoked), scanned A, original, MIT.

A company-research workflow that uses Exa to find information about companies, competitors, news, financials, and LinkedIn profiles. It can also build lists of companies.

In plain words
What is it for?
Use it for competitor analysis, market research, company research, or creating company lists.
Why use it?
It gathers several kinds of company information for research tasks that would otherwise require searching many sources separately. It supports both individual company research and broader market lists.

Skill for Claude Code

Written for Claude Code: context: fork in frontmatter.

Good fit Use it for competitor analysis, market research, company research, or creating company lists.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/exa-labs/agent-skills/company-research
Install

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.

Any agent
npx skills add exa-labs/agent-skills --skill company-research
Clone the repo
git clone --depth 1 https://github.com/exa-labs/agent-skills

Made for: Claude Code.

Wrote 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.

agentmods badge for company-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/exa-labs/agent-skills/company-research/github.svg)](https://agentmods.dev/skills/exa-labs/agent-skills/company-research)
Your own site
<a href="https://agentmods.dev/skills/exa-labs/agent-skills/company-research"><img src="https://agentmods.dev/badge/skills/exa-labs/agent-skills/company-research/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.

agentmods 80×15 button for company-research

Your own site · 80×15
<a href="https://agentmods.dev/skills/exa-labs/agent-skills/company-research"><img src="https://agentmods.dev/badge/skills/exa-labs/agent-skills/company-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 46 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,467 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 20 Jul 2026
  • Snyk warn 20 Jul 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00046 $0.01467
Opus 5.5 $0.00018 $0.00587
Sonnet 5.5 $0.00009 $0.00293
Haiku 4.5 $0.00005 $0.00147

Measured 18d ago against content hash 94c935e953e4, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 18d 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.

skills/company-research/SKILL.md · 149 lines

How it starts

The opening of the file, as written. The whole thing — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Company Research

Tool Selection (Critical)

Two Exa surfaces, two jobs:

  • Exa Agent (agent_run) — the default for company research. Use it for deep dives, competitor analysis, multi-angle research (product + funding + news + people), and building company lists. One Agent run handles query decomposition, multi-step searching, and synthesis internally — do not orchestrate many manual searches for work an Agent run covers.
  • web_search_advanced_exa — quick, low-latency lookups: a fast category: "company" discovery pass, a single news check, or finding a homepage.

Do NOT use other Exa tools.

Deep Dives and Lists: Exa Agent

Agent runs may stream to completion in one call. If a run outlives the MCP call window, continue waiting with its returned run ID.

  1. Call agent_run with a natural-language query and, when you want repeatable structure, an outputSchema (bound arrays with maxItems).
  2. If it returns status: "running" with a runId, call agent_run again with only that runId until outputReady is true.
  3. Read output.text or output.structured, plus output.grounding citations, from the agent_run result.

Useful inputs: systemPrompt (source preferences, dedup rules), input.exclusion (companies to avoid), previousRunId (a new follow-up run based on a completed run), effort ("low" default; "auto" or "high" for more depth).

Example: company deep dive

agent_run {
  "query": "Research Anthropic: product lines, funding history and valuation, key executives, main competitors, and notable news from the last 6 months.",
  "effort": "auto",
  "outputSchema": {
    "type": "object",
    "properties": {
      "overview": { "type": "string" },
      "funding": { "type": "array", "maxItems": 10, "items": { "type": "object", "properties": { "round": { "type": "string" }, "amount": { "type": "string" }, "date": { "type": "string" } }, "required": ["round"] } },
      "competitors": { "type": "array", "maxItems": 10, "items": { "type": "string" } },
      "key_people": { "type": "array", "maxItems": 10, "items": { "type": "object", "properties": { "name": { "type": "string" }, "title": { "type": "string" } }, "required": ["name", "title"] } }
    },
    "required": ["overview", "competitors"]
  }
}

Read the full file on GitHub · 149 lines

Changes

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.

  1. 18d ago Changed 94c935e953e4
  2. 2mo ago First seen · 149 lines · 46 tokens per session scan A 20f819119fe3

Subscribe to this mod's changes

company-research is a skill published in the GitHub repository exa-labs/agent-skills (65 stars, last pushed yesterday), licensed MIT. It adds 46 tokens to every session and 1,467 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-30.

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