Rent Comp Intake
Ingests inbound rent comp observations (shopped, 3rd-party, operator-reported), validates, normalizes, proposes updates to market_rent_benchmark files, and opens an approval if the magnitude delta crosses the overlay threshold. Follows the reference update flow end to end.
What this skill does
Rent Comp Intake is an A.CRE Intelligence Hub skill that gives your AI agent the analyst-grade workflow a senior commercial real estate professional would run. Ingests inbound rent comp observations (shopped, 3rd-party, operator-reported), validates, normalizes, proposes updates to market_rent_benchmark files, and opens an approval if the magnitude delta crosses the overlay threshold. Follows the reference update flow end to end. Ingests inbound rent comp observations shopped, 3rd-party, operator-reported , validates, normalizes, proposes updates to market rent benchmark files, and opens an approval if the magnitude delta crosses the overlay threshold. Follows the reference update flow end to end. Activate it inside ChatGPT, Claude, Manus, or OpenClaw by saying something like "Use the Rent Comp Intake skill" — the Hub routes the request to this skill and the underlying primary-source CRE data feeds backends automatically. Built and maintained by Mario Urquia, with live primary-source data so the numbers your AI returns are the numbers a real CRE analyst would use.
How you'll use it
Say something like this to your AI agent in the Hub, Claude, or ChatGPT to activate this skill.
Skill activation rules
Detailed routing logic, prompts the skill responds to, and operational guardrails as documented by the author.
Ingests inbound rent comp observations (shopped, 3rd-party, operator-reported), validates, normalizes, proposes updates to market_rent_benchmark files, and opens an approval if the magnitude delta crosses the overlay threshold. Follows the reference update flow end to end.
What's inside
Rent Comp Intake
Workflow purpose
Take a raw rent comp observation and move it through the reference layer's update flow so market rent benchmarks stay live. Ingest, validate, normalize, propose, approve (when needed), derive.
Trigger conditions
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Rent Comp Intake
Workflow purpose
Take a raw rent comp observation and move it through the reference layer's update flow so market rent benchmarks stay live. Ingest, validate, normalize, propose, approve (when needed), derive.
Trigger conditions
- Explicit: "I shopped X property; capture comps", "new 3rd-party export", "log comps from call".
- Implicit:
workflows/market_rent_refreshdetects a comp bundle; PM drops raw data intoreference/raw/rent_comp/. - Recurring: ad hoc; any market-survey cycle.
Inputs (required / optional)
| Input | Type | Required | Notes |
|---|---|---|---|
| Raw comp records | table / json | required | property, unit_type, asking rent, concessions, source |
| Normalization rules | yaml | required | overlay |
| Current market_rent_benchmark | csv | required | to compute delta |
Outputs
Full instructions and any reference files ship in the .skill bundle.
rent-comp-intake/ └── SKILL.md # Required: instructions + metadata
How to run it
Not in the Hub? Download the .skill bundle above and follow the A.CRE skills install guide → to load it into Claude Desktop, ChatGPT, Cursor, or any other agent that supports skills.
Already in the Hub. If you're an AI.Edge Pro or A.CRE Accelerator member, this skill is bundled into the A.CRE Intelligence Hub direct connector (MCP server) — just ask your agent.