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Glama

DaedalMap Population Estimates

Get Catalog

get_catalog
Read-only

Free discovery. Returns the list of live agent-ready data packs available on DaedalMap.

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

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, so the description's claim of returning data is consistent. It adds context by specifying the returned items are 'live agent-ready' and from 'DaedalMap', but does not describe pagination, limits, or output structure beyond a list.

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 two short sentences, front-loaded with the purpose ('Free discovery') and immediately specifying the return value. Every word contributes.

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?

Given the tool is simple (no parameters, no output schema, one sibling tool type), the description adequately covers the purpose. However, it could be improved by hinting at the relationship with get_pack (e.g., 'Use this to browse available packs, then get_pack to retrieve a specific pack').

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 tool has 0 parameters, so by baseline the description does not need to add parameter semantics. The description mentions 'Free discovery' which aligns with no inputs, but no additional value is needed beyond the schema.

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 verb 'Returns' and the resource 'list of live agent-ready data packs available on DaedalMap', distinguishing it from siblings like 'get_pack' (which likely retrieves a single pack) and 'query_dataset' (which queries dataset content).

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 'Free discovery' implies a browse/search use case, but there is no explicit guidance on when to use this tool versus alternatives (get_pack, query_dataset). No 'when not to use' is provided.

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 has a distinct role: get_catalog lists packs, get_pack returns one pack's metadata, get_tool_help explains MCP facade tools, and query_dataset executes data queries. There is no meaningful overlap between list, detail, help, and query actions.

Naming Consistency4/5

Three tools use the clear get_<noun> pattern, and query_dataset is another verb_noun imperative. The only minor deviation is switching from get_ to query_, but the naming remains predictable and consistent in style.

Tool Count5/5

Four tools are well-scoped for the discovery-and-query workflow of a data-pack MCP server: catalog, pack details, tool guidance, and dataset querying. No tool feels redundant, and the count is comfortably within the ideal range.

Completeness5/5

The server covers the full read-only lifecycle: discover available packs, inspect a pack's metadata and usage, understand the query contract, and run a dataset query. No obvious operation is missing for its stated purpose.