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Glama

analyze_ticket

Read-only

Gather city-specific evidence for a parking violation, including ticket details, registration cross-ref, Street View, traffic rules, defenses, and dispute history.

Instructions

Gather evidence for a specific violation: ticket details, registration cross-ref, Street View imagery, traffic rule lookup, common defenses, and past dispute history

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityYesWhich city issued the ticket
violation_numberYesThe violation/ticket number

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered. The description adds meaningful behavioral scope beyond that by disclosing the composite data sources it pulls (registration cross-ref, Street View, rule lookup, defenses, dispute history), which tells the agent this is a multi-source aggregation, not a simple lookup.

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?

A single front-loaded sentence with no filler; the evidence enumeration is dense but each item conveys what the tool returns. Slightly list-heavy but appropriately sized.

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?

With no output schema, the description usefully describes the return content by enumerating the evidence categories. Combined with annotations covering the safety profile, an agent has enough to call this correctly; minor gaps remain around result format and failure behavior.

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 100% with only two parameters (city enum and violation_number), both documented in the schema. The description adds no syntax, format, or constraint detail beyond what the schema already provides, so the baseline 3 applies.

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?

States a specific verb ('Gather evidence') and resource ('a specific violation'), then enumerates the evidence types, so the agent knows this is a composite read/analysis tool. It is distinguishable from siblings like check_tickets and generate_dispute, though it never names them.

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?

Usage is only implied: gathering evidence suggests it precedes a dispute generation step, but the description never states when to call this versus check_tickets, check_status, or generate_dispute, nor any prerequisites or exclusions.

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