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/.agents/skills/add-county/SKILL.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/skills/chadru/assessor-lookup-public/add-county)<a href="https://agentmods.dev/skills/chadru/assessor-lookup-public/add-county"><img src="https://agentmods.dev/badge/skills/chadru/assessor-lookup-public/add-county/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/chadru/assessor-lookup-public/add-county"><img src="https://agentmods.dev/badge/skills/chadru/assessor-lookup-public/add-county.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 | $0.00050 | $0.00640 |
| Opus 5 | $0.00025 | $0.00320 |
| Sonnet 5 | $0.00010 | $0.00128 |
| Haiku 4.5 | $0.00005 | $0.00064 |
Grade A, and why
add-county 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.
How it starts
The opening of the file, as written. The whole thing — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Add a new county
Goal: a new county client that returns the standard record dict, wired into the registry, and verified with a golden record — added in a bounded change (one client module + one registry entry + one golden case).
Steps
-
Check discovery first.
discover_county(county, state)(MCP) orassessor-lookup discover "<County>" --state <st>. If it resolves to a tier-1 source, verify with a reallookup_propertyand you may be done. If it only hits the tier-2 baseline (owner/legal/value, no building data), continue. -
Map the site. Delegate to the explorer agent with the county and a sample property. It returns, API-first, the platform, exact requests, and the field-name mapping — and confirms whether the building fields (GLA/beds/baths/ year) are available. Honor its verdict: prefer a JSON API; scrape only if no API carries the building data.
-
Implement the client at
platforms/<name>.py(config-driven platform) orjurisdictions/<country>/<state>/<name>.py(bespoke driver exposingbuild(entry, timeout=, verbose=)): a class whoselookup(address)(and ideallylookup_by_parcel(parcel_id)) returns the standard record dict with astatuskey, never raising on failure. Mirror the closest existing client:jurisdictions/us/co/adams.py(ArcGIS JSON),platforms/spatialest.py(Spatialest JSON), orplatforms/eagleweb.py(scrape). -
Wire it in. For a new platform, add one line to the
PLATFORMSdict inplatforms/__init__.py; then add thecounty_registry.jsonentry (a config-only jurisdiction needs just the entry). -
Pin a golden. Add a case to
DEFAULT_CASESinassessor_lookup/harness.py, thenpython tests/harness.py --capture --filter <case-id>. Use a real single-family home (not a vacant lot or HOA tract) so building fields are exercised. -
Verify. Hand off to the reviewer agent (live site + golden + parser correctness). Then confirm
pytest -m "not network"andpython tests/harness.py --filter <case-id>are green.
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 · 49 lines · 50 tokens per session scan A 8955af43b7ff
add-county is a skill published in the GitHub repository chadru/assessor-lookup-public (6 stars, last pushed 1mo ago), licensed MIT. It adds 50 tokens to every session and 640 once invoked, about $0.0003 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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