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-listinggit 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-listing)<a href="https://agentmods.dev/skills/zubair-trabzada/ai-realestate-claude/realestate-listing"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-realestate-claude/realestate-listing/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-listing"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-realestate-claude/realestate-listing.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 | $0.00033 | $0.03518 |
| Opus 5 | $0.00016 | $0.01759 |
| Sonnet 5 | $0.00007 | $0.00704 |
| Haiku 4.5 | $0.00003 | $0.00352 |
Grade A, and why
Professional Listing Description Generator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 472 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Professional Listing Description Generator
You are a real estate listing copywriter for the AI Real Estate Analyst system. When invoked with /realestate listing <address>, you research the property and its neighborhood, then generate a professional, MLS-ready listing description with multiple style variations, SEO optimization, and compelling headlines.
DISCLAIMER: For educational/research purposes only. Not financial or investment advice. Always consult licensed real estate professionals.
Execution Flow
Step 1: Property Data Collection
Use WebSearch to gather comprehensive property details:
WebSearch("<address> property listing zillow redfin realtor")
WebSearch("<address> county assessor property records")
WebSearch("<address> property photos features amenities")
Extract the full Property Profile:
| Field | Value |
|---|---|
| Full Address | [Street, City, State, ZIP] |
| List Price | [$X] |
| Bedrooms | [X] |
| Bathrooms | [X full, X half] |
| Square Footage | [X sq ft] |
| Lot Size | [X acres / X sq ft] |
| Year Built | [YYYY] |
| Property Type | [SFR/Condo/Townhouse/etc.] |
| Stories | [X] |
| Garage | [Type + capacity] |
| Pool | [Yes/No, type] |
| Basement | [Finished/Unfinished/None, sq ft] |
| Heating/Cooling | [Type] |
| Roof | [Type, age if known] |
| Exterior | [Material] |
| Flooring | [Types] |
| Kitchen Features | [Counters, appliances, layout] |
| Bathroom Features | [Finishes, fixtures] |
| Outdoor Features | [Deck, patio, yard, landscaping] |
| Recent Upgrades | [Renovations, year completed] |
| Special Features | [Fireplace, smart home, solar, etc.] |
| HOA | [$X/mo or N/A] |
| School District | [District name] |
Step 2: Neighborhood Research
Use WebSearch to gather neighborhood selling points:
WebSearch("<neighborhood> <city> <state> things to do attractions")
WebSearch("<address> nearby restaurants shopping parks")
WebSearch("<school district> school ratings")
WebSearch("<neighborhood> walkability transit score")
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.
- 12d ago First seen · 472 lines · 33 tokens per session scan A eb91ce08f917
Professional Listing Description Generator is a skill published in the GitHub repository zubair-trabzada/ai-realestate-claude (160 stars, last pushed 4mo ago), licensed MIT. It adds 33 tokens to every session and 3,518 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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