A workflow for adding a county property-data source when automatic discovery cannot find a usable one. It produces the standard property record and verifies it with a known test case.

Use it to investigate a county's website or API, implement its lookup client, register it, and test it with a golden record.

It provides a bounded way to add missing county support while checking whether the source includes building details such as size, bedrooms, bathrooms, and year built.

How chadru/assessor-lookup-public configures Claude Code and Codex

Reuse

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.

Copy the file

curl -O https://raw.githubusercontent.com/chadru/assessor-lookup-public/codex/public-release/.agents/skills/add-county/SKILL.md

Clone the repo

git clone --depth 1 https://github.com/chadru/assessor-lookup-public

Made for: Claude Code, Codex.

Wrote this? Show the measurements

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README.md

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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.

Your own site · 80×15

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Per session 50 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 640 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

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 5.5	$0.00020	$0.00256
Sonnet 5.5	$0.00010	$0.00128
Haiku 4.5	$0.00005	$0.00064

Measured 2mo ago against content hash 8955af43b7ff, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 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.

.agents/skills/add-county/SKILL.md · 49 lines

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) or assessor-lookup discover "<County>" --state <st>. If it resolves to a tier-1 source, verify with a real lookup_property and 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) or jurisdictions/<country>/<state>/<name>.py (bespoke driver exposing build(entry, timeout=, verbose=)): a class whose lookup(address) (and ideally lookup_by_parcel(parcel_id)) returns the standard record dict with a status key, never raising on failure. Mirror the closest existing client: jurisdictions/us/co/adams.py (ArcGIS JSON), platforms/spatialest.py (Spatialest JSON), or platforms/eagleweb.py (scrape).
Wire it in. For a new platform, add one line to the PLATFORMS dict in platforms/__init__.py; then add the county_registry.json entry (a config-only jurisdiction needs just the entry).
Pin a golden. Add a case to DEFAULT_CASES in assessor_lookup/harness.py, then python 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" and python tests/harness.py --filter <case-id> are green.

Read the full file on GitHub · 49 lines

Changes

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 · 49 lines · 50 tokens per session scan A 8955af43b7ff

Subscribe to this mod's changes

add-county is a skill published in the GitHub repository chadru/assessor-lookup-public (6 stars, last pushed 3mo ago), licensed MIT. It adds 50 tokens to every session and 640 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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assessor-lookup-public: Skill for Claude Code