nyc-acris

nyc-acris is a skill for Claude Code from AlpacaLabsLLC/skills-for-architects. It costs 36 tokens per session (1,495 once invoked), scanned A, original, MIT.

A lookup tool for New York City’s ACRIS property records, which record deeds, mortgages, liens, sales, and ownership history.

In plain words
What is it for?
Use it for property due diligence, ownership checks, and reviewing a building’s recorded sales, mortgages, liens, or deeds.
Why use it?
It helps you check a property’s recorded transactions and ownership without searching several public datasets by hand. It does not cover building permits or violations.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: positional $N argument; mentions Claude Code; mentions Codex.

Part of the as plugin — 46 skills, 7 agents, 3 hooks shipped together

Good fit Use it for property due diligence, ownership checks, and reviewing a building’s recorded sales, mortgages, liens, or deeds.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/alpacalabsllc/skills-for-architects/nyc-acris
Install

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.

Any agent
npx skills add AlpacaLabsLLC/skills-for-architects --skill nyc-acris
Clone the repo
git clone --depth 1 https://github.com/AlpacaLabsLLC/skills-for-architects

Made for: Claude Code.

Or install as, the plugin that ships this one along with the rest of its 46 skills, 7 agents, 3 hooks.

Wrote 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.

agentmods badge for nyc-acris

README.md
[![agentmods](https://agentmods.dev/badge/skills/alpacalabsllc/skills-for-architects/nyc-acris/github.svg)](https://agentmods.dev/skills/alpacalabsllc/skills-for-architects/nyc-acris)
Your own site
<a href="https://agentmods.dev/skills/alpacalabsllc/skills-for-architects/nyc-acris"><img src="https://agentmods.dev/badge/skills/alpacalabsllc/skills-for-architects/nyc-acris/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.

agentmods 80×15 button for nyc-acris

Your own site · 80×15
<a href="https://agentmods.dev/skills/alpacalabsllc/skills-for-architects/nyc-acris"><img src="https://agentmods.dev/badge/skills/alpacalabsllc/skills-for-architects/nyc-acris.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 36 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,495 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. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 6 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Prompt Injection · line 13
    Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.
    Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
  • medium Data Exfiltration · line 40
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 47
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 54
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 63
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 102
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
How audits are shown
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 $0.00036 $0.01495
Opus 5 $0.00018 $0.00747
Sonnet 5 $0.00007 $0.00299
Haiku 4.5 $0.00004 $0.00150

Measured 12d ago against content hash 94033b2e4323, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

nyc-acris 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.

skills/nyc-acris/SKILL.md · 126 lines

How it starts

The opening of the file, as written. The whole thing — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/as:nyc-acris — ACRIS Property Transaction Records

Harness note: use /as:<skill> on Claude Code and $<skill> on Codex. Resolve <skill-root> as the directory containing this loaded SKILL.md and <plugin-root> as the plugin root that contains skills/, and use equivalent native tools when host tool names differ.

Look up ACRIS (Automated City Register Information System) property records — deeds, mortgages, liens, and other recorded documents. Uses a 3-table join across Legals, Master, and Parties datasets. No API key required.

Usage

/as:nyc-acris 120 Broadway, Manhattan
/as:nyc-acris 1000770001          (BBL)
/as:nyc-acris 1001389             (BIN)

Steps 1–2: Parse Input & Resolve BBL

Read ../nyc-property-report/pluto-resolution.md (shared by all 7 NYC due-diligence skills) and follow it: parse the input (address, BBL, or BIN) and resolve via PLUTO.

This skill's delta: parsing the BBL into separate boro/block/lot components (per the shared file) is REQUIRED — the ACRIS Legals table has no combined BBL field. BIN resolution is only needed when the user's input was a BIN.

Step 3: Query ACRIS (3-Table Join)

Dataset IDs and field names are canonical in ../nyc-property-report/socrata-reference.md — on any disagreement, the reference wins.

IMPORTANT: ACRIS requires BBL (not BIN). The Legals table uses separate borough, block, lot fields — not a combined BBL field.

Step 3a: Get Document IDs from Legals Table

https://data.cityofnewyork.us/resource/8h5j-fqxa.json?borough={boro}&block={block}&lot={lot}&$order=good_through_date DESC&$limit=20

Extract document_id from each row. These are the join keys for the next two queries.

Step 3b: Get Document Details from Master Table

Build a $where clause with the document_ids from Step 3a:

https://data.cityofnewyork.us/resource/bnx9-e6tj.json?$where=document_id IN ('{id1}','{id2}','{id3}',...)&$order=document_date DESC

Key fields: document_id, record_type, crfn, doc_type, document_date, document_amt, recorded_datetime (NOT doc_date/doc_amount/recorded_filed — those fields don't exist and 400)

Read the full file on GitHub · 126 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 12d ago First seen · 126 lines · 36 tokens per session scan A 94033b2e4323

Subscribe to this mod's changes

nyc-acris is a skill published in the GitHub repository AlpacaLabsLLC/skills-for-architects (353 stars, last pushed 8d ago), licensed MIT. It adds 36 tokens to every session and 1,495 once invoked, about $0.0002 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 2026-08-30.

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