get_packFree discovery. Returns detailed metadata, coverage, freshness, preferred canonical tool guidance, and first-query examples for one pack. Call this before querying a new pack so you can see time shape, coverage limits, and the paste-ready first query.
| Name | Required | Description | Default |
|---|---|---|---|
| pack_id | Yes | Pack identifier from get_catalog. Newly catalog-admitted packs require no MCP schema change. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds 'Free discovery' and output content context, but it does not disclose additional behavioral traits such as rate limits, response structure, or potential side effects. This is adequate but not rich.
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?
Two sentences with no filler. The core action and output contents are front-loaded, the usage timing is stated clearly, and every clause earns its place.
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?
For a simple read-only lookup with one required parameter, the description covers what is returned, when to call it, and where the pack_id comes from. It is slightly vague about how the returned 'canonical tool guidance' should be used, but nothing critical for invoking the tool is missing.
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?
Schema description coverage is 100%, so the schema already documents pack_id as a pack identifier from get_catalog. The description reinforces that the tool operates on 'one pack' but adds no meaningful parameter semantics beyond the schema. Baseline 3 applies.
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 uses a specific verb ('Returns') and clearly identifies the resource ('one pack') along with the kind of information provided ('metadata, coverage, freshness, preferred canonical tool guidance, and first-query examples'). It does not explicitly differentiate from sibling tools like get_catalog, but the 'one pack' framing makes the per-pack lookup intent clear.
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 description gives an explicit usage directive: 'Call this before querying a new pack.' This tells the agent when to invoke the tool and why. It does not mention exclusions or alternatives, so it falls short of a full 5.
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 clearly distinct purpose: catalog lists packs, get_pack returns pack metadata, get_tool_help explains tool usage, query_dataset executes data queries, and search_disaster_links discovers cross-disaster relationships. There is no meaningful overlap or ambiguity between them.
All tool names follow a consistent lowercase snake_case verb_noun pattern: get_catalog, get_pack, get_tool_help, query_dataset, search_disaster_links. The verb differences reflect different action types, but the structural pattern is uniform.
Five tools is well-scoped for a data-access MCP server. The set covers discovery, metadata retrieval, tool guidance, querying, and relationship search without unnecessary bulk or redundancy.
The tool surface covers the full discovery-to-query workflow: find packs, inspect pack metadata, get tool help, query datasets, and search disaster link families. A minor gap is the lack of dataset-level schema or status tools, but these are partly covered by get_pack metadata and are not critical for the server's read-oriented purpose.