Small Business Intelligence by Brick & Mortar

by io.github.2016judea

Twin Cities Datasets

twin_cities_datasets

Read-onlyIdempotent

Lists the public-records datasets Brick & Mortar publishes for the seven-county Minneapolis-St. Paul metro, with real row counts, column names, the filtered cuts available, and the counties each one actually covers. Free, no account. Call this FIRST to learn what can be answered, then call twin_cities_records to ask it. These are joined county and federal records — parcels and lot lines, recorded sale prices, owners, rental licences, contamination files, business counts by trade, census tracts.

Example invocations:

"What Twin Cities property data do you have access to?"
"Is there anything on contamination or storage tanks in Minneapolis?"
"What columns are in the recorded-sales dataset?"

Input Schema

Name	Required	Description	Default
`about`	No	Optional plain-words filter — 'sales', 'who owns it', 'contamination'. Matches dataset titles and subjects. Omit to list everything.

Output Schema

Name	Required	Description
`tool`	Yes
`answer`	Yes
`centre`	No
`notice`	No	Present ONLY when the request was denied by usage policy instead of executed. When present, no other field carries a result.
`sample`	No	At most six example rows. Never report these as the complete result.
`caveats`	Yes
`columns`	No
`dataset`	No
`subject`	No
`coverage`	No	The counties this dataset actually holds. Coverage is not uniform across datasets.
`datasets`	No
`scope_label`	No
`download_url`	No	A free sample of the file; the full file is sold (the sample's first line says where).
`documented_at`	No	Page documenting this dataset's source, full column list and stated limits.
`matching_rows`	No	The true number of rows that match. `sample` shows at most six of them.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 20, 2026

changedOutput schema / properties / download_url / description

Previous value: -"Fetch this for the complete file."New value: +"A free sample of the file; the full file is sold (the sample's first line says where)."

First observedSep 1, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare the safety profile (readOnly, idempotent, non-destructive, open-world), so the bar is lower. The description adds genuinely useful context beyond them: 'Free, no account,' and that results include real row counts, column names, filtered cuts, and county coverage. It does not, however, mention any rate limits or output size, leaving a small gap.

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, then usage routing, then a descriptive list of contents, with example invocations at the end. Every element earns its place, though the example list is somewhat redundant with the already-clear purpose statement.

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

Completeness4/5

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

An output schema exists, so return values needn't be spelled out, yet the description still characterizes the payload (row counts, column names, cuts, counties). Combined with annotations, an agent has everything needed to call correctly; only the lack of output-size or rate-limit guidance keeps it from a 5.

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

Parameters3/5

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

Schema coverage is 100%, so the single 'about' parameter is already fully documented in the schema. The description does not elaborate on filter syntax or matching behavior beyond what the schema provides, so the baseline of 3 is appropriate.

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 (Lists) and resource (public-records datasets) with precise scope (seven-county Minneapolis-St. Paul metro). It clearly distinguishes itself from twin_cities_records by naming it as the follow-up tool, so an agent can route without opening either 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 instructs 'Call this FIRST to learn what can be answered, then call twin_cities_records to ask it,' giving both the ordering and the named alternative. Example invocations reinforce exactly the situations where this tool applies.

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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