browserbase-company-research

browserbase-company-research is a skill for Claude Code, Codex from ItamarZand88/awesome-agent-conventions. It costs 0 tokens per session (2,963 once invoked), scanned B, original, MIT.

A company-research skill that finds potential customers, studies their businesses and target audiences, and produces a scored research report and CSV file. It uses Browserbase Search API, a web-search service, for discovery.

In plain words
What is it for?
Use it to find companies to sell to, research prospects, identify companies matching an ideal customer profile, build a target-company list, or conduct market research.
Why use it?
It combines company discovery and deeper investigation in one workflow, so prospect research does not have to be assembled manually from scattered sources.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: reads .claude/ paths; mentions subagents; names the AskUserQuestion tool.

Good fit Use it to find companies to sell to, research prospects, identify companies matching an ideal customer profile, build a target-company list, or conduct market research.

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Install with agentmods
npx agentmods add skills/itamarzand88/awesome-agent-conventions/browserbase-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 ItamarZand88/awesome-agent-conventions --skill browserbase-company-research
Clone the repo
git clone --depth 1 https://github.com/ItamarZand88/awesome-agent-conventions

Made for: Claude Code, Codex.

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 browserbase-company-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/itamarzand88/awesome-agent-conventions/browserbase-company-research/github.svg)](https://agentmods.dev/skills/itamarzand88/awesome-agent-conventions/browserbase-company-research)
Your own site
<a href="https://agentmods.dev/skills/itamarzand88/awesome-agent-conventions/browserbase-company-research"><img src="https://agentmods.dev/badge/skills/itamarzand88/awesome-agent-conventions/browserbase-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 browserbase-company-research

Your own site · 80×15
<a href="https://agentmods.dev/skills/itamarzand88/awesome-agent-conventions/browserbase-company-research"><img src="https://agentmods.dev/badge/skills/itamarzand88/awesome-agent-conventions/browserbase-company-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,963 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00000 $0.02963
Opus 5 $0.00000 $0.01482
Sonnet 5 $0.00000 $0.00593
Haiku 4.5 $0.00000 $0.00296

Measured 12d ago against content hash e0ba1f9b0b9f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade B, and why

browserbase-company-research scanned grade B with 1 finding 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.

Reads agent configuration directoriesmediumAgent snooping

.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.

**First-run setup**: On the first run you'll be prompted to approve `browse cloud fetch`, `browse cloud search`, `cat`, `mkdir`, `sed`, etc. Select **"Yes, and don't ask again for: browse cloud fetch:\*"** (or equivalent
conventions/skill-md/examples/data-analysis/browserbase-company-research/SKILL.md · 216 lines

How it starts

The opening of the file, as written. The whole thing — 216 lines — stays where its author put it; the contents beside it link to each section on GitHub.


name: company-research description: | Company discovery and deep research skill. Researches a company's product and ICP, discovers target companies to sell to using Browserbase Search API, deeply researches each using a Plan→Research→Synthesize pattern, and scores ICP fit — compiled into a scored research report and CSV. Supports depth modes (quick/deep/deeper) for balancing scale vs intelligence. Use when the user wants to: (1) find companies to sell to, (2) research potential customers, (3) discover companies matching an ICP, (4) build a target company list, (5) do market research on prospects. Triggers: "find companies to sell to", "company research", "find prospects", "ICP research", "target companies", "who should we sell to", "market research", "lead research", "prospect list". license: MIT compatibility: Requires browse CLI (npm install -g browse) and BROWSERBASE_API_KEY env var allowed-tools: Bash Agent metadata: author: browserbase version: "1.1.0"

Company Research

Discover and deeply research companies to sell to. Uses Browserbase Search API for discovery and a Plan→Research→Synthesize pattern for deep enrichment — outputting a scored research report and CSV.

Required: BROWSERBASE_API_KEY env var and browse CLI installed.

First-run setup: On the first run you'll be prompted to approve browse cloud fetch, browse cloud search, cat, mkdir, sed, etc. Select "Yes, and don't ask again for: browse cloud fetch:*" (or equivalent) for each to auto-approve for the session. To permanently approve, add these to your ~/.claude/settings.json under permissions.allow:

"Bash(browse:*)", "Bash(bunx:*)", "Bash(bun:*)", "Bash(node:*)",
"Bash(cat:*)", "Bash(mkdir:*)", "Bash(sed:*)", "Bash(head:*)", "Bash(tr:*)", "Bash(rm:*)"

Path rules: Always use the full literal path in all Bash commands — NOT ~ or $HOME (both trigger "shell expansion syntax" approval prompts). Resolve the home directory once and use it everywhere. When constructing subagent prompts, replace {SKILL_DIR} with the full literal path.

Output directory: All research output goes to ~/Desktop/{company_slug}_research_{YYYY-MM-DD}/. This directory contains one .md file per researched company plus a final .csv. The user gets both the scored spreadsheet and the full research files on their Desktop.

CRITICAL — Tool restrictions (applies to main agent AND all subagents):

  • All web searches: use browse cloud search. NEVER use WebSearch.
  • All page content extraction: use node {SKILL_DIR}/scripts/extract_page.mjs "<url>". This script fetches via browse cloud fetch --output, parses title + meta tags + visible body text, and automatically falls back to browse get markdown when fetch fails or returns thin JS-rendered content. NEVER hand-roll a browse cloud fetch | sed pipeline — it strips meta tags and doesn't parse the stdout JSON envelope. NEVER use WebFetch.
  • All research output: subagents write one markdown file per company to {OUTPUT_DIR}/{company-slug}.md using bash heredoc. NEVER use the Write tool or python3 -c. See references/example-research.md for the file format.
  • Report + CSV compilation: use node {SKILL_DIR}/scripts/compile_report.mjs {OUTPUT_DIR} --open — generates HTML report and CSV in one step, opens overview in browser.
  • URL deduplication: use node {SKILL_DIR}/scripts/list_urls.mjs /tmp after discovery.
  • Subagents must use ONLY the Bash tool. No other tools allowed.
  • Main agent NEVER reads raw discovery JSON batch files. Use list_urls.mjs for dedup.

CRITICAL — Anti-hallucination rules (applies to main agent AND all subagents):

  • NEVER infer product_description, industry, or target_audience from a site's fonts, framework (Framer/Next.js/React), design system, or typography. These are cosmetic and say nothing about what the company sells.
  • NEVER let the user's own ICP leak into a target's description. If you don't know what the target does, write Unknown — do not pattern-match them onto the ICP.
  • product_description MUST quote or paraphrase a specific phrase from extract_page.mjs output (TITLE, META_DESCRIPTION, OG_DESCRIPTION, HEADINGS, or BODY). If none of those fields yield a recognizable product statement, write Unknown — homepage content not accessible.
  • If product_description is Unknown, cap icp_fit_score at 3 and set icp_fit_reasoning to Insufficient evidence — homepage returned no readable content.

Read the full file on GitHub · 216 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. 12d ago First seen · 216 lines · 0 tokens per session scan B e0ba1f9b0b9f

Subscribe to this mod's changes

browserbase-company-research is a skill published in the GitHub repository ItamarZand88/awesome-agent-conventions (31 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,963 tokens. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.