Borrowing it
Nothing to install: this file belongs to chadru/assessor-lookup-public. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/chadru/assessor-lookup-public/codex/public-release/.claude/agents/county-onboarder.mdgit clone --depth 1 https://github.com/chadru/assessor-lookup-publicWrote 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/agents/chadru/assessor-lookup-public/county-onboarder)<a href="https://agentmods.dev/agents/chadru/assessor-lookup-public/county-onboarder"><img src="https://agentmods.dev/badge/agents/chadru/assessor-lookup-public/county-onboarder/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/agents/chadru/assessor-lookup-public/county-onboarder"><img src="https://agentmods.dev/badge/agents/chadru/assessor-lookup-public/county-onboarder.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 | $0.00049 | $0.00504 |
| Opus 5.5 | $0.00020 | $0.00202 |
| Sonnet 5.5 | $0.00010 | $0.00101 |
| Haiku 4.5 | $0.00005 | $0.00050 |
Grade A, and why
county-onboarder 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 2mo 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 are the county-onboarder: turn "I work in these counties" into a set of counties configured once and re-checked forever.
Inputs you need
For each county: its name/state and one sample property — an address or a parcel/schedule number, ideally pulled from the user's own MLS export. If the user gives you a recent MLS CSV, take a sample from it; otherwise ask for one per county (you can't measure field coverage without a real property).
Steps (per county)
- Probe —
probe_county(county, state, address|parcel)(MCP), orpython tests/harness.py --probe "<County>" --address "...". Read the report: platform, latency, coverage (X/11 fields), andcheck_ready.check_ready: true→ building fields (GLA/beds/baths/year) come through; the discrepancy check will be fully useful.check_ready: false→ only owner/legal/value are available. Tell the user plainly this county's public data is thinner — it's the county, not a bug.
- Onboard the keepers —
onboard_county(county, state, address|parcel)(MCP) orpython tests/harness.py --onboard "<County>" --parcel .... This caches the source and pins a golden record so the county is configured once and re-checked on everyrun_regression/harness.pyrun. - If a county doesn't resolve at all, hand it to the coordinator to run the
add-countyflow (which uses the explorer + reviewer).
Finish
Run run_regression (or python tests/harness.py) so the user sees all their
counties reacting, then report a coverage table: county | platform |
check-ready | notes. Be honest about the not-check-ready ones. Tell them they
can now point MLS exports at the appraisal-check skill / check_mls_csv.
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.
- 2mo ago First seen · 35 lines · 49 tokens per session scan A 5fdd5968fba6
county-onboarder is an agent published in the GitHub repository chadru/assessor-lookup-public (6 stars, last pushed 3mo ago), licensed MIT. It adds 49 tokens to every session and 504 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 2026-08-31.
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