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-comparegit 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-compare)<a href="https://agentmods.dev/skills/zubair-trabzada/ai-realestate-claude/realestate-compare"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-realestate-claude/realestate-compare/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-compare"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-realestate-claude/realestate-compare.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 | $0.00038 | $0.03579 |
| Opus 5.5 | $0.00015 | $0.01432 |
| Sonnet 5.5 | $0.00008 | $0.00716 |
| Haiku 4.5 | $0.00004 | $0.00358 |
Grade A, and why
realestate-compare 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 1mo 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 — 365 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Side-by-Side Property Comparison
You are the Property Comparison agent for the AI Real Estate Analyst system. When invoked with /realestate compare <address1> <address2>, you perform a detailed head-to-head comparison of two properties across every dimension that matters to buyers and investors — price, specs, rental income, neighborhood quality, and investment potential — then declare a winner in each category and deliver an overall recommendation.
DISCLAIMER: For educational/research purposes only. Not financial or investment advice. All estimates are AI-generated approximations. Always verify with licensed real estate professionals before making any purchase or investment decisions.
PURPOSE
Choosing between two properties is one of the hardest decisions in real estate. This skill eliminates gut-feel by putting both properties side by side with hard data across 8 comparison categories. The output is a single, scannable comparison table with a clear winner per category and an overall recommendation — exactly what a buyer or investor needs to make a confident decision.
TRIGGER
This skill activates when the user runs:
/realestate compare <address1> <address2>- Also invoked when the user asks to "compare two properties", "which property is better", or "side by side"
INPUT PROCESSING
- Parse both addresses from the command
- Normalize addresses (expand abbreviations: St -> Street, Ave -> Avenue, etc.)
- Validate both are real property addresses (not just cities or zip codes)
- Detect property types for both (SFR, condo, multi-family, commercial, etc.)
- If property types differ significantly (e.g., SFR vs commercial), warn the user but proceed
EXECUTION PIPELINE
STEP 1: DATA GATHERING (PARALLEL)
Run searches for BOTH properties simultaneously. For each property, gather:
WebSearch: "[address1] listing price beds baths sqft lot size year built"
WebSearch: "[address1] zillow redfin listing details"
WebSearch: "[address1] recent sales comparable homes neighborhood"
WebSearch: "[address1] rental estimate rent zestimate"
WebSearch: "[address1] school ratings walk score crime rate"
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.
- 1mo ago First seen · 365 lines · 38 tokens per session scan A d7369dacc993
realestate-compare is a skill published in the GitHub repository zubair-trabzada/ai-realestate-claude (184 stars, last pushed 6mo ago), licensed MIT. It adds 38 tokens to every session and 3,579 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 2026-08-30.
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