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DaedalMap Population Estimates

by com.daedalmap

Query Dataset

query_dataset
Read-only

Generic structured query for direct source_id or pack_id access using the same contract as POST /api/v1/query/dataset. Free packs: currency, distributed_manufacturing, floods, nri, owid, un_sdg, un_wpp, volcanoes, world_bank_wdi. Paid packs: earthquakes, hurricanes, tornadoes, tsunamis, wildfires, world_factbook, worldpop (x402 Base USDC).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNoOptional sort instructions for row-returning queries.
limitNoMaximum number of rows to return for the requested source or pack.
outputNoOptional output controls such as response format hints.
filtersNoStructured filters including time, region_ids, and compare clauses.
metricsNoMetric ids to return. Use event_count for aggregate counts when supported.
pack_idNoPack identifier from get_catalog. Newly catalog-admitted packs require no MCP schema change.
source_idNoConcrete source id such as 'earthquakes_events', 'volcanoes_events', 'hurricanes_events', or 'un_sdg/01'.
request_idNoOptional caller-supplied request id for tracing and idempotency.

TDQS

A3.8/5.0
Behavior4/5

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

With readOnlyHint=true, the safety profile is already known. The description adds meaningful context by disclosing that some packs are paid, pricing in x402 Base USDC, and that it follows an existing API contract. It does not mention rate limits or other runtime behaviors, but the added cost and pack-access details are valuable.

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 compact and front-loaded with the core purpose, followed by a concise enumeration of free and paid packs. Every sentence contributes useful information without redundancy or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For an 8-parameter query tool with no output schema, the description gives good pack context but does not explain response format, default query behavior, or whether exactly one of source_id/pack_id is required. Referencing an external API contract helps but does not fully compensate for these gaps.

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?

Schema coverage is 100%, so parameters are already documented well. The description adds value by enumerating actual free and paid pack identifiers and indicating direct access by source_id or pack_id, which helps an agent identify concrete valid inputs beyond the generic schema descriptions.

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 states that this tool performs a structured query for direct source_id or pack_id access, referencing the same contract as POST /api/v1/query/dataset. It is specific about the resource and operation, but it does not explicitly compare against sibling tools like get_catalog or get_pack.

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 provides useful context about available free and paid packs, which implies when this tool can be used, and the schema notes that pack_id comes from get_catalog. However, it does not explicitly state when to prefer this tool over alternatives or when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All DaedalMap Population Estimates toolsInspect
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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.

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