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 ItamarZand88/awesome-agent-conventions --skill browserbase-company-researchgit clone --depth 1 https://github.com/ItamarZand88/awesome-agent-conventionsWrote 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/itamarzand88/awesome-agent-conventions/browserbase-company-research)<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.
<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>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 | $0.00000 | $0.02963 |
| Opus 5 | $0.00000 | $0.01482 |
| Sonnet 5 | $0.00000 | $0.00593 |
| Haiku 4.5 | $0.00000 | $0.00296 |
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 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 viabrowse cloud fetch --output, parses title + meta tags + visible body text, and automatically falls back tobrowse get markdownwhen fetch fails or returns thin JS-rendered content. NEVER hand-roll abrowse cloud fetch | sedpipeline — 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}.mdusing bash heredoc. NEVER use the Write tool orpython3 -c. Seereferences/example-research.mdfor 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 /tmpafter discovery. - Subagents must use ONLY the Bash tool. No other tools allowed.
- Main agent NEVER reads raw discovery JSON batch files. Use
list_urls.mjsfor dedup.
CRITICAL — Anti-hallucination rules (applies to main agent AND all subagents):
- NEVER infer
product_description,industry, ortarget_audiencefrom 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_descriptionMUST quote or paraphrase a specific phrase fromextract_page.mjsoutput (TITLE, META_DESCRIPTION, OG_DESCRIPTION, HEADINGS, or BODY). If none of those fields yield a recognizable product statement, writeUnknown — homepage content not accessible.- If
product_descriptionisUnknown, capicp_fit_scoreat 3 and seticp_fit_reasoningtoInsufficient evidence — homepage returned no readable content.
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 · 216 lines · 0 tokens per session scan B e0ba1f9b0b9f
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.
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