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lts_filters

Get available filter values for LTS queries. Returns distinct regions and cities from the verification queue. Optionally filter cities by region. Use this before calling lts_queue or lts_search with region/city filters to get valid values.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
regionNoIf provided, only return cities within this region

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations provided, the description carries the transparency burden. It discloses that the tool returns distinct regions and cities from the verification queue, optionally filtered by region. This gives useful behavioral context beyond a simple 'get filters' statement, though it doesn't describe the output format or edge cases.

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 four concise, purposeful sentences. It front-loads the purpose, then covers the resource, optional parameter, and usage guidance with no redundancy or 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 tool with one optional parameter and no output schema, the description is largely complete. It covers purpose, usage, and parameter semantics. However, it omits the response structure (e.g., whether the result is an array or an object), which would be useful given no output schema is present.

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 schema covers the region parameter, but the description adds semantic value by clarifying that regions are always returned while the region parameter filters only the cities. This goes beyond the schema's description of 'only return cities within this region.'

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 clearly states the tool's function: 'Get available filter values for LTS queries.' It specifies the resource (LTS queries) and the output (distinct regions and cities from the verification queue), distinguishing it from sibling data-query tools like lts_search or lts_by_region.

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?

The description gives explicit usage context: 'Use this before calling lts_queue or lts_search with region/city filters to get valid values.' It names alternatives and specifies the timing, satisfying the requirement for when-to-use guidance.

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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TDQS

A4.2/5.0
Disambiguation5/5

Each tool targets a distinct aspect of LTS data (by city, developer, law, region, etc.) with no overlapping purposes. The descriptions clearly delineate their unique use cases.

Naming Consistency5/5

All tools follow the consistent pattern 'lts_<descriptive_noun_or_phrase>' using snake_case. The naming is uniform and predictable, aiding agent selection.

Tool Count5/5

With 12 tools, the set is well-scoped for a data query and analysis server. Each tool serves a clear function without redundancy or overload.

Completeness5/5

The tool set covers all necessary query dimensions (city, developer, law, region, expiry, stats, trends) and includes a search, check, and project-level view. No obvious gaps for a read-only analytics server.

Resources