Get Catalog
get_catalogFree discovery. Returns the list of live agent-ready data packs available on DaedalMap.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
get_catalogFree discovery. Returns the list of live agent-ready data packs available on DaedalMap.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds context beyond the readOnlyHint annotation by emphasizing 'Free discovery' and 'live agent-ready data packs', which clarifies the nature of the data returned. It does not mention any side effects, auth requirements, or rate limits, but given the read-only annotation and zero parameters, the behavior is transparent enough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that immediately conveys the tool's purpose. Every word adds value, and there is no redundancy or filler. It is an excellent model of conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no params, read-only, no output schema), the description provides a clear picture of what the tool returns and on what platform. It does not detail the structure of the returned list, but for a catalog discovery tool, the description is adequate and complete enough for an agent to select and invoke it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With no parameters and 100% schema coverage (vacuously), the description does not need to explain parameters. The baseline for zero parameters is 4, and the description appropriately focuses on the tool's output rather than input semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: it returns a list of live agent-ready data packs on DaedalMap. The verb 'returns' and the specific resource ('data packs') make the purpose explicit. It is distinct from siblings like get_pack (retrieving a specific pack) and query_dataset (querying data).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use is implied: it is a discovery tool to list available data packs. However, the description does not explicitly state when to use it versus alternatives, nor does it mention any exclusions or prerequisites. With siblings like get_pack, explicit guidance would improve clarity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a distinct purpose: catalog discovery, pack metadata retrieval, tool guidance, dataset querying, and cross-disaster link search. There is no overlap or ambiguity that would cause an agent to misselect a tool.
All tool names follow a consistent verb_noun snake_case pattern (get_catalog, get_pack, get_tool_help, query_dataset, search_disaster_links), with clear prefixes indicating action type. The naming is uniform and predictable.
Five tools is a well-scoped set for a data discovery and query server. Each tool earns its place, covering discovery, help, generic querying, and cross-event relationship search without unnecessary overlap or bloat.
The tool set covers the full lifecycle of data access: discovery (get_catalog, get_pack), guidance (get_tool_help), querying (query_dataset), and cross-disaster linkage (search_disaster_links). There are no obvious gaps that would hinder an agent from accomplishing its tasks.