Cubi Estate

Daily raise statistics

raise_stats

Read-only

Daily-raise (new listings/day) for the Cubi corpus, SALE/RENT split — aggregate counts only, no listings.

Complements corpus_stats (which has no transaction split). Table-ready:
per-country today / yesterday / trailing-7-completed-day sale+rent, plus the
top-15 providers by 7-day new-listing volume with their sale/rent split.
(The 21-day per-country chart SERIES stays with corpus_stats — scanning
21 days of country/txn heap here is too slow for an interactive tool.)

Served from precomputed MVs refreshed a few times a day (never a live scan),
so it is instant; `refreshed_at` is when the underlying data was last rebuilt.

Returns:
    JSON string: {today:"YYYY-MM-DD", days_completed:int, refreshed_at:"… UTC",
    all:{today,yest,sale7,rent7,total7},
    countries:[{country,today,yest,sale7,rent7,total7}] (desc by total7),
    providers:[{src,sale,rent,total}]}. "all" sums every country incl null.

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 1, 2026

TDQS

A4.8/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly/openWorld=false/destructive=false, but the description adds substantive behavior: data is served from precomputed MVs refreshed a few times a day, never a live scan, so it is instant, and refreshed_at marks the underlying rebuild time. This is exactly the kind of staleness/freshness context the annotations cannot convey.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core purpose before the corpus_stats comparison, then the return shape. It runs a bit long with the parenthetical latency justification, but every clause carries routing or freshness information, so little is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite an output schema existing, the description still sketches the return payload (all/countries/providers with field meanings and sort order) plus the MV-refresh caveat. For a complex multi-section aggregate tool, nothing an agent needs to call or interpret it is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, so the baseline is 4. There is no parameter surface to clarify, and the description correctly does not invent one.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource (daily-raise / new listings per day for the Cubi corpus) with explicit scope (SALE/RENT split, aggregate counts only, no listings). It names the sibling corpus_stats and explains precisely how it differs. An agent can select this tool without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly positions against corpus_stats: this tool has the transaction split that corpus_stats lacks, and the 21-day per-country series intentionally stays with corpus_stats for latency reasons. Both the when-to-use and the boundary case are spelled out.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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