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 chrisdothtml/ai-job-finder --skill find-companiesgit clone --depth 1 https://github.com/chrisdothtml/ai-job-finderWrote 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/chrisdothtml/ai-job-finder/find-companies)<a href="https://agentmods.dev/skills/chrisdothtml/ai-job-finder/find-companies"><img src="https://agentmods.dev/badge/skills/chrisdothtml/ai-job-finder/find-companies/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/chrisdothtml/ai-job-finder/find-companies"><img src="https://agentmods.dev/badge/skills/chrisdothtml/ai-job-finder/find-companies.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 | $0.00031 | $0.00367 |
| Opus 5 | $0.00015 | $0.00183 |
| Sonnet 5 | $0.00006 | $0.00073 |
| Haiku 4.5 | $0.00003 | $0.00037 |
Grade A, and why
find-companies 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.
What it actually says
You can fetch https://companiesmarketcap.com/tech/largest-tech-companies-by-market-cap to get an HTML document, which you'll need to reason about. The document should contain a table containing rows with info about tech companies. Your job is to find this list of companies and extract them into a list of just the company names. You should see a pagination link (e.g. "Next") below the list of jobs. Get the next page as well so we have a decent amount to work with.
From there, you need to figure out if they have jobs posted on commonly-used job posting sites (please do this in a single python script to avoid the user needing to confirm many commands):
- Greenhouse: fetch
https://boards-api.greenhouse.io/v1/boards/{COMPANY_NAME}to determine whether the company has jobs listed on Greenhouse - Lever: run a HEAD request to
https://jobs.lever.co/{COMPANY_NAME}(to keep requests lightweight) to determine whether the company has jobs listed on lever - Ashby: fetch
https://api.ashbyhq.com/posting-api/job-board/{COMPANY_NAME}— returns 200 if the company has an Ashby board, 404 if not. (Do NOT use a HEAD request tojobs.ashbyhq.com— that site is a SPA and returns 200 for all paths regardless of whether the company exists.)
Then write any companies you found, along with their jobs board type to src/analysis/companies.ts. Do NOT modify the Typescript types in this file.
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 · 15 lines · 31 tokens per session scan A 112a124494a0
find-companies is a skill published in the GitHub repository chrisdothtml/ai-job-finder (3 stars, last pushed 1mo ago), licensed MIT. It adds 31 tokens to every session and 367 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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