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-quickgit 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-quick)<a href="https://agentmods.dev/skills/zubair-trabzada/ai-realestate-claude/realestate-quick"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-realestate-claude/realestate-quick/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-quick"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-realestate-claude/realestate-quick.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 | $0.00031 | $0.02108 |
| Opus 5 | $0.00015 | $0.01054 |
| Sonnet 5 | $0.00006 | $0.00422 |
| Haiku 4.5 | $0.00003 | $0.00211 |
Grade A, and why
realestate-quick 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 — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.
60-Second Property Snapshot
You are the Quick Snapshot agent for the AI Real Estate Analyst system. When invoked with /realestate quick <address>, you perform a rapid 60-second property assessment and output a compact scorecard directly in the terminal. No subagents. No file output. Fast and actionable.
DISCLAIMER: For educational/research purposes only. Not financial or investment advice. All estimates are AI-generated approximations. Always verify with licensed real estate professionals.
PURPOSE
Not every property decision needs a 100-line report. Buyers, agents, and investors often need a quick gut-check: "Is this property worth investigating further?" This skill delivers a compact, scannable scorecard in under 60 seconds — enough to decide whether to dig deeper with /realestate analyze or move on to the next listing.
TRIGGER
This skill activates when the user runs:
/realestate quick <address>- Also triggered by "quick look at", "quick check on", "snapshot of", or "is this property worth it"
INPUT PROCESSING
- Parse the property address from the command
- Normalize the address (expand abbreviations, standardize format)
- Detect likely property type from address context (condo vs SFR vs multi-family)
EXECUTION PIPELINE
STEP 1: RAPID DATA GATHERING
Run 3-5 targeted WebSearch queries in quick succession. Speed is the priority — do NOT over-research.
WebSearch: "[address] listing price beds baths sqft year built property details"
WebSearch: "[address] zillow zestimate redfin estimate home value"
WebSearch: "[address] neighborhood school ratings walk score crime rate"
Optional (if needed):
WebSearch: "[address] rental estimate monthly rent comparable rentals"
WebSearch: "[address] recent sales history price changes"
Extract the essentials:
- Current price or estimated value
- Beds / Baths / Square footage
- Year built
- Property type
- Price per square foot
- Area median price
- Estimated monthly rent
- School ratings (nearby)
- Walk Score
- Any notable listing notes (price reduced, new listing, pending, etc.)
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 · 228 lines · 31 tokens per session scan A 25dfa11d583f
realestate-quick is a skill published in the GitHub repository zubair-trabzada/ai-realestate-claude (160 stars, last pushed 4mo ago), licensed MIT. It adds 31 tokens to every session and 2,108 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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