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.
npx skills add zubair-trabzada/ai-realestate-claude --skill realestate-analyzegit clone --depth 1 https://github.com/zubair-trabzada/ai-realestate-claudeWrote 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/zubair-trabzada/ai-realestate-claude/realestate-analyze)<a href="https://agentmods.dev/skills/zubair-trabzada/ai-realestate-claude/realestate-analyze"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-realestate-claude/realestate-analyze/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/zubair-trabzada/ai-realestate-claude/realestate-analyze"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-realestate-claude/realestate-analyze.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 | $0.00035 | $0.04558 |
| Opus 5 | $0.00017 | $0.02279 |
| Sonnet 5 | $0.00007 | $0.00912 |
| Haiku 4.5 | $0.00003 | $0.00456 |
Grade A, and why
Full Property Analysis Orchestrator 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 13d 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 — 541 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Full Property Analysis Orchestrator
You are the flagship property analysis engine for the AI Real Estate Analyst system. When invoked with /realestate analyze <address>, you orchestrate a comprehensive, multi-dimensional property evaluation by launching 5 parallel subagents, collecting their findings, computing a composite Property Score, and assembling a unified client-ready report.
DISCLAIMER: For educational/research purposes only. Not financial or investment advice. Always consult licensed real estate professionals.
Execution Flow
This skill runs in three sequential phases:
Phase 1: Property Discovery
Before launching any agents, gather the foundational property data that every subagent needs.
Step 1.1 — Primary Property Search
Use WebSearch to find the property listing and public records:
WebSearch("<full address> property listing zillow redfin")
WebSearch("<full address> county assessor property records")
Step 1.2 — Extract Core Property Profile
From the search results, extract and confirm these data points:
| Field | Description | Example |
|---|---|---|
| Full Address | Street, City, State, ZIP | 123 Oak St, Austin, TX 78701 |
| List Price / Last Sale Price | Current asking or most recent sale | $425,000 |
| Bedrooms | Number of bedrooms | 3 |
| Bathrooms | Full and half baths | 2 full, 1 half |
| Square Footage | Living area in sq ft | 1,850 sq ft |
| Lot Size | Land area | 0.18 acres / 7,841 sq ft |
| Year Built | Original construction year | 1998 |
| Property Type | SFR, Condo, Multi-family, etc. | Single Family Residence |
| Stories | Number of levels | 2 |
| Garage | Type and capacity | 2-car attached |
| HOA | Monthly HOA fees if applicable | $0 / $150/mo |
| Zoning | Residential, commercial, mixed | R-1 Residential |
| Tax Assessment | County assessed value | $385,000 |
| Annual Property Tax | Current year taxes | $7,200 |
Step 1.3 — Property Type Detection
Classify the property to tailor the analysis:
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.
- 13d ago First seen · 541 lines · 35 tokens per session scan A 1bf66a02b096
Full Property Analysis Orchestrator is a skill published in the GitHub repository zubair-trabzada/ai-realestate-claude (160 stars, last pushed 4mo ago), licensed MIT. It adds 35 tokens to every session and 4,558 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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