idx-cma-report_skill

This skill generates defensible CMA reports and interactive value views from IDX data, helping agents estimate ranges and present comps confidently.

Python

2.6k

GitHub Stars

2

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill openclaw/skills --skill idx-cma-report

_meta.json284 B
SKILL.md2.8 KB

Overview

This skill generates comparative market analysis (CMA) and home valuation reports from IDX listing data and selected comparable properties. It produces a defensible valuation package: structured calculations, a written agent/client report, and an interactive prompt for Google Gemini Canvas or Google AI Studio. Use it to streamline comp selection, document adjustments, and publish an interactive CMA experience.

How this skill works

The skill ingests subject-property details and candidate comparables pulled via the IDX MCP/CLI, normalizes data to a CMA JSON schema, and prompts the user to confirm 3–8 comps. A build script generates a markdown report, calculation payload, local interactive HTML, and a Gemini/AI Studio prompt. The output includes estimated market range, central estimate, adjustment explanations, and a checklist for publishing the interactive view.

When to use it

Preparing a seller-facing home evaluation or listing presentation
Estimating a defensible market value range for negotiations
Creating an interactive CMA experience for clients via Google tools
Documenting valuation adjustments and confidence factors
Converting IDX search results into a standardized CMA package

Best practices

Pull closed, pending, and active comps, then ask the user to confirm final set (default 3–8 comps)
Normalize inputs to the provided CMA JSON schema to ensure consistent calculations
Explicitly flag missing or low-quality fields and avoid inventing values
Explain major adjustments in plain language and show the math behind the range
Use the generated Gemini prompt and cma_data.json to publish an interactive, shareable CMA

Example use cases

Agent prepares a listing presentation: pull comps, produce report, hand client the interactive CMA
Brokerage quality-control: generate standardized CMAs across multiple agents for comparability
Pricing strategy: test multiple comp sets and document how adjustments change the value range
Client follow-up: send the interactive Gemini Canvas link so buyers/sellers can explore comps and notes

FAQ

No. The outputs support broker/agent CMAs and are not a substitute for a licensed appraisal; always disclose that distinction.

How many comps should I include?

Default is 3–8 comps. Include enough similar, recent comps to justify adjustments; ask the user if a different count is preferred.

Can I publish an interactive CMA?

Yes. Use the generated gemini_canvas_prompt.md and cma_data.json in Google AI Studio or Gemini Canvas to build a sortable comp table, map-ready view, value visualizations, and shareable output.