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Glama

Drone Intelligence products

get_products

The commercial products, machine-readable: what they are, prices, checkout URLs, licence terms.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It indicates that the output is 'machine-readable' and includes specific data fields, which is useful context. However, it does not disclose any side effects, permissions, or limitations, leaving some behavioral ambiguity.

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, concise sentence that front-loads the key information (commercial products, machine-readable, specific data fields). There is no unnecessary verbosity, and it is appropriately sized for the tool's simplicity.

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 tool with no parameters and no output schema, the description provides sufficient context about the returned content (prices, checkout URLs, licence terms). It could be more explicit about the action (e.g., 'returns' or 'retrieves') and output format, but it is reasonably complete for a simple read-only tool.

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 input schema has zero parameters, so there are no parameter semantics to clarify. Per the rubric, a baseline of 4 is appropriate when there are no parameters, and the description does not need to compensate for missing schema details.

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 clearly identifies the resource (commercial products) and the scope of returned data (prices, checkout URLs, licence terms). The verb 'get' is implied by the tool name rather than stated explicitly, and it does not distinguish itself from the sibling tool 'list_catalogue', but the scope is specific enough to be useful.

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 description implies usage (retrieving product information) but provides no explicit guidance on when to choose this tool over siblings like 'list_catalogue' or 'get_intelligence_page'. There is no mention of alternatives or exclusions, so it is minimally adequate.

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

A3.7/5.0
Disambiguation5/5

Each tool targets a distinct resource or operation. Content tools (get_briefing, get_company_profile, get_intelligence_page, compare_companies) are clearly separated by content type, while tracker_* tools each serve a unique data query function. There is no ambiguity between content retrieval and tracker analysis.

Naming Consistency3/5

Content tools follow a verb_noun pattern (get_*, compare_companies, list_catalogue, search_content), but tracker_* tools use a noun-prefix style (tracker_aggregate, tracker_awards, tracker_capital_ledger). This mixed convention is internally consistent within each group but not throughout the server.

Tool Count5/5

12 tools is well-scoped for a server covering both content access and a tracker dataset. Each tool has a clear purpose, and the number aligns with the guideline of 3-15 tools.

Completeness5/5

The tool surface covers all announced content types (briefing, intelligence page, company profile, comparison) with get/compare operations, plus catalogue listing and cross-type search. The tracker tools provide comprehensive querying and metadata access, with no obvious missing operations.

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