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.
git clone --depth 1 https://github.com/HasData/indeed-mcpWrote 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/commands/hasdata/indeed-mcp/hiring-map)<a href="https://agentmods.dev/commands/hasdata/indeed-mcp/hiring-map"><img src="https://agentmods.dev/badge/commands/hasdata/indeed-mcp/hiring-map/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/commands/hasdata/indeed-mcp/hiring-map"><img src="https://agentmods.dev/badge/commands/hasdata/indeed-mcp/hiring-map.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 | $0.00016 | $0.00242 |
| Opus 5.5 | $0.00006 | $0.00097 |
| Sonnet 5.5 | $0.00003 | $0.00048 |
| Haiku 4.5 | $0.00002 | $0.00024 |
Grade A, and why
hiring-map 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 23d 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
Map the hiring for one role.
Ask me for the role and the cities if I have not given them. Three to five cities keeps the answer readable.
Then:
- For each city call
hasdata_indeed_listing_getJobListingswith the role inkeyword, the city inlocationandsort: "date", so recent postings come first. - Per city report how many openings came back, the employers posting the most, and the salary range across the postings that carry one.
- Say how many postings published a salary and how many did not. A range built on four of forty postings is a weak signal, and the reader deserves to know that.
- List the ten most recent openings across all cities with title, company, city, salary where present and the posting date.
- Note any employer that appears in more than one city, since that is usually the interesting pattern.
Do not open individual postings unless I ask for a description. If a city returns an empty list, say so plainly instead of padding the table with another city's rows.
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.
- 23d ago First seen · 18 lines · 16 tokens per session scan A a8f09647f237
hiring-map is a command published in the GitHub repository HasData/indeed-mcp (11 stars, last pushed 4d ago), licensed MIT. It adds 16 tokens to every session and 242 once invoked, about $0.0001 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 2026-09-23.
Other commands, from other repositories
profile-brief
A brief on a public Instagram account and what it has been posting.
hotel-shortlist
A shortlist of Booking.com hotels for a destination, dates and party.
zillow-comps
Comparable sales for an address or an area, pulled from Zillow.
tiktok-pulse
What an account posts on TikTok and which videos actually performed.
stay-shortlist
A shortlist of Airbnb stays for a destination, dates and party size.
ddg-baseline
An unpersonalised ranking for a query, used as a baseline.