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erincheong

Underground Utility Permit Review MCP Server

by erincheong

Search permit cases

search_permits
Read-onlyIdempotent

Search and filter pending excavation permits by street, city, applicant, project type, verdict, or risk level. Get summaries to triage risks; retrieve full details with get_permit.

Instructions

Search and filter pending excavation permit cases. Use this to find permits by street, city, applicant, project type, permit verdict, or risk level. Returns a summary of each match, not the full utility line detail — call get_permit for that.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNoExact city filter, e.g. 'Bellflower, CA'.
limitNoMaximum results to return. Default 10.
queryNoFree text matched against street name, city, scope, applicant, and permit ID.
verdictNoFilter by the permit's current verdict.
min_riskNoOnly permits at or above this crossing-risk band.
only_flaggedNoOnly permits with at least one line flagged for field verification.
project_typeNoHigh-level project category.
contains_utility_typeNoOnly permits with at least one line of this utility type near the excavation.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
permitsYes
matchCountYes
totalPermitsYes
filtersAppliedNo
Behavior4/5

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

With readOnlyHint=true and destructiveHint=false already in annotations, the description adds scope ('pending') and return shape ('summary of each match, not the full utility line detail'). It doesn't discuss rate limits or side effects, but annotations cover the safety profile, so this is adequate.

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?

Two sentences, front-loaded purpose, then usage, then a pointer to get_permit. Every clause earns its place; no filler.

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?

The tool is a search/filter operation with no required params and an output schema, so the description doesn't need to explain return structure. It covers the main purpose, the pending-case scope, and directs to get_permit for deeper detail. This is fully sufficient for an agent to select and invoke the tool.

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?

All 8 parameters have descriptions in the schema (100% coverage), and the description merely restates a few filter criteria without adding new semantics. The schema already explains query, verdict, min_risk, etc., so the description adds marginal value.

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?

The description uses a specific verb+resource ('Search and filter pending excavation permit cases') and lists concrete search dimensions (street, city, applicant, project type, permit verdict, risk level). It also distinguishes itself from the sibling get_permit by noting it returns summaries rather than full detail.

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 says 'Use this to find permits by...' and provides an alternative path for full detail with 'call get_permit for that.' This gives clear when-to-use and a named alternative, though it doesn't contrast with the other sibling tools.

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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