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Count matching permits

count_permits
Read-only

How many permits match a search (area, category, city, zip, dates, minimum value) before paying for the records. Free.

Input Schema

NameRequiredDescriptionDefault
zipNo
cityNoCity name, case-insensitive
sinceNoIssued on or after (YYYY-MM-DD)
untilNoIssued on or before (YYYY-MM-DD)
categoryNoPermit category, e.g. roof, pool, solar, hvac, new_residential
minValueNoMinimum job valuation in USD
jurisdictionYesArea id, e.g. new-york-ny, miami-dade-fl. Use list_coverage for names.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already establish readOnlyHint=true and openWorldHint=false, so the safety profile is clear. The description adds valuable behavioral context by noting the call is 'Free' and that it is a preview before paying for records, which is not captured in the structured annotations.

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

Conciseness5/5

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

The description is a single front-loaded sentence that immediately states the count behavior and the free/paid context. Every phrase adds useful information with no filler.

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?

For a simple count tool with high schema coverage and annotations, the description is nearly complete: it implies a numeric result and explains the free preview behavior. It could be slightly stronger by mentioning the required jurisdiction or using the exact parameter name 'jurisdiction' instead of 'area', but the gaps are minor.

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 description coverage is 86%, so the schema already documents nearly all parameters. The description lists the same search facets (area, category, city, zip, dates, minimum value) without adding syntax, defaults, or constraints beyond what the schema provides; baseline 3 is appropriate.

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

Purpose4/5

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

The description states a specific verb and resource ('How many permits match a search') and lists the search facets, so the agent can tell this is a counting tool. It does not explicitly name or contrast with sibling tools like search_permits or permit_stats, leaving some differentiation implicit.

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

Usage Guidelines3/5

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

The phrase 'before paying for the records' gives a clear use context: check the count before purchasing records. However, it never explicitly names search_permits or states when to use count_permits versus permit_stats or permit_trends, so guidance is implied rather than 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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