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Cubi Estate

Daily new-listing statistics

get_daily_new_listing_stats
Read-only

How many NEW listings Cubi added per day, by country and by source, split into sale and rent — aggregate counts only, no listings.

Use it to answer "how much new inventory is arriving" questions: today,
yesterday and the last 7 completed days, per country, plus the 15 sources
contributing the most new listings over those 7 days.

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

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint/openWorldHint/destructiveHint), so the bar is lower, and the description adds genuinely new behavioral context: it is served from precomputed MVs refreshed a few times a day, never a live scan, so it is instant, and refreshed_at is explained. Deducting slightly because part of the block is return-format detail that duplicates the output schema rather than expanding behavior.

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

Conciseness3/5

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

Front-loaded and readable, but it is long: the 'Table-ready:' paragraph restates content already given in the opening and in the routing sentence, and the Returns block duplicates the output schema. Several sentences do not earn their place.

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?

For a no-parameter, read-only aggregate tool whose annotations carry the safety profile, everything an agent needs is present: what it returns, freshness/latency, the sibling it complements, and the scope it excludes. Output schema exists, so the description's extra return detail is surplus rather than necessary.

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 and the description correctly makes no parameter claims, which is the expected baseline of 4. Nothing to mis-describe.

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 precise verb, resource and scope ('how many NEW listings added per day, by country and source, split sale/rent, aggregate counts only') and explicitly carves out territory it does not own ('no listings', 21-day series stays with corpus_stats). An agent can distinguish it from corpus_stats and data_layer_stats 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?

Gives an explicit when-to-use trigger ('how much new inventory is arriving' questions) and names the alternative tool with the condition that selects it ('Complements corpus_stats, which has no transaction split'), plus a stated exclusion (21-day chart series). Routing guidance is complete.

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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