assessor-lookup-public: Instructions file for Codex

AGENTS.md

assessor-lookup-public AGENTS.md is an instructions file for Codex, OpenCode from chadru/assessor-lookup-public. It costs 3,869 tokens per session, scanned A, original, MIT.

Contributor instructions for Assessor Lookup Public, a command-line tool that collects and parses public property-assessment records from different local government services.

In plain words
What is it for?
Use them when changing property-record parsers, jurisdiction support, the command-line entry point, or related tests.
Why use it?
They explain installation, testing, benchmarking, live-network tests, and the project’s platform-specific architecture.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: mentions Claude Code; mentions AGENTS.md; mentions Codex.

This is chadru/assessor-lookup-public's own configuration. It tells Codex and OpenCode how to work on assessor-lookup-public itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything assessor-lookup-public configures →

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.md
Clone the repo
git clone --depth 1 https://github.com/chadru/assessor-lookup-public

Made for: Codex, OpenCode.

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Per session 3,869 This file is loaded in full into every session.
When invoked 3,869 The same file — it is already loaded in full.
Security scan A 1 finding. 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.03869 $0.03869
Opus 5 $0.01935 $0.01935
Sonnet 5 $0.00774 $0.00774
Haiku 4.5 $0.00387 $0.00387

Measured 10d ago against content hash 950a504e9f62, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

assessor-lookup-public AGENTS.md scanned grade A with 1 finding 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 10d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

There is no build/lint tooling configured — this is a stdlib-only package. All HTTP uses `urllib`; **do not add `requests` or other runtime dependencies** to the core (`dependencies = []` in `pyproject.toml` is intention
Origin

Copies of this mod

1 near-identical copy found in the catalogue:

AGENTS.md · 95 lines

How it starts

The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

This file provides guidance to Codex (Codex.ai/code) when working with code in this repository.

Commands

# Install for development (stdlib-only core; extras are optional)
pip install -e ".[dev]"            # + pytest
pip install -e ".[card]"           # + playwright, then: playwright install chromium

# Run the test suite (network tests deselected by default in most workflows)
pytest                             # all tests
pytest -m "not network"            # skip tests that hit live county APIs
pytest -m network                  # only the live-API integration tests
pytest tests/platforms/test_spatialest.py::TestSpatialestRecordcardParsesFields   # single class
pytest tests/platforms/test_spatialest.py::TestFieldNameVariants::test_parse_sqft_sfla  # single test

# Benchmark + golden-record regression harness (live county endpoints)
python tests/harness.py            # full run: regression + latency + discovery + parser bench
python tests/harness.py --capture  # (re)pin golden records after legitimate data changes
python tests/harness.py --filter clear   # only cases matching a substring
python tests/harness.py --offline        # parser micro-bench only, no network
pytest -m network tests/test_golden_live.py   # same goldens as pytest

# CLI (installed as the `assessor-lookup` entry point)
assessor-lookup lookup "123 Main St" --county "El Paso"
assessor-lookup lookup --parcel 5227004002 --county Adams --json
assessor-lookup counties
assessor-lookup check subject.csv comps.csv --county "El Paso"

There is no build/lint tooling configured — this is a stdlib-only package. All HTTP uses urllib; do not add requests or other runtime dependencies to the core (dependencies = [] in pyproject.toml is intentional). Playwright is confined to the optional [card] extra and imported lazily inside card.py.

Architecture

The package turns a street address or parcel number into a normalized property-record dict, and diffs that record against MLS CSV data. Two layers:

Read the full file on GitHub · 95 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.

  1. 10d ago First seen · 95 lines · 3,869 tokens per session scan A 950a504e9f62

Subscribe to this mod's changes

assessor-lookup-public AGENTS.md is an instructions file published in the GitHub repository chadru/assessor-lookup-public (6 stars, last pushed 1mo ago), licensed MIT. It adds 3,869 tokens to every session, about $0.0193 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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