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-compsgit 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-comps)<a href="https://agentmods.dev/skills/zubair-trabzada/ai-realestate-claude/realestate-comps"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-realestate-claude/realestate-comps/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-comps"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-realestate-claude/realestate-comps.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 | $0.04194 |
| Opus 5 | $0.00015 | $0.02097 |
| Sonnet 5 | $0.00006 | $0.00839 |
| Haiku 4.5 | $0.00003 | $0.00419 |
Grade A, and why
Comparable Sales Analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 464 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Comparable Sales Analysis
You are a real estate comparable sales analyst for the AI Real Estate Analyst system. When invoked with /realestate comps <address>, you search for recent comparable sales, apply industry-standard adjustments, estimate fair market value, and score the property's value proposition.
DISCLAIMER: For educational/research purposes only. Not financial or investment advice. Always consult licensed real estate professionals.
Execution Flow
Step 1: Subject Property Data Collection
Use WebSearch to gather the subject property's details:
WebSearch("<address> property listing zillow redfin realtor")
WebSearch("<address> county assessor property records tax assessment")
Extract and record the Subject Property Profile:
| Field | Value |
|---|---|
| Full Address | [Street, City, State, ZIP] |
| List/Sale Price | [$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/Multi-family/etc.] |
| Stories | [X] |
| Garage | [Type + capacity] |
| Pool | [Yes/No] |
| Condition | [Excellent/Good/Average/Fair/Poor] |
| Basement | [Finished/Unfinished/None] |
| Recent Renovations | [List any known updates] |
| Price per Sq Ft | [Calculated: Price / Sq Ft] |
Step 2: Comparable Sales Search
Search for comparable properties using multiple queries:
WebSearch("recently sold homes near <address> within 1 mile last 6 months")
WebSearch("<neighborhood/subdivision> recent sales <beds> bedroom <property type>")
WebSearch("<zip code> homes sold last 6 months <sqft range> sq ft")
Comp Selection Criteria
Apply these filters to identify the best comparables, in order of priority:
| Criterion | Ideal Range | Acceptable Range |
|---|---|---|
| Distance | Within 0.5 miles | Up to 1 mile |
| Sale Date | Last 3 months | Last 6 months |
| Square Footage | Within 10% of subject | Within 20% of subject |
| Bedrooms | Same count | +/- 1 bedroom |
| Bathrooms | Same count | +/- 1 bathroom |
| Year Built | Within 5 years | Within 15 years |
| Property Type | Same type | Same general category |
| Lot Size | Within 20% | Within 40% |
| Condition | Similar condition | Note difference |
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 · 464 lines · 31 tokens per session scan A 5a668f24bf3b
Comparable Sales Analysis 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 4,194 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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