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DaedalMap Distributed Manufacturing Locations

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

A4.1/5.0
Behavior4/5

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

Annotations declare readOnlyHint=true, so the read-only nature is covered. The description adds the free vs paid pack distinction and the pricing reference (x402 Base USDC), which is valuable behavioral context beyond annotations, such as potential access restrictions.

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?

Two sentences, front-loaded with purpose, and the pack list is compact. No fluff; every part contributes to understanding the tool's scope and the available data sources.

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?

The tool is complex with optional nested parameters and no output schema, but the description doesn't explain response format or provide example queries beyond the API contract reference. It's adequate but not complete for a generic query tool, leaving the agent to rely on the referenced contract.

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 descriptions cover all 8 parameters (100% coverage), so the baseline is 3. The description adds concrete pack ids and refers to the API contract, enriching understanding of pack_id and the overall query structure beyond what the schema provides.

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 states a specific verb ('query'), a resource (dataset via source_id or pack_id), and references the exact API contract (POST /api/v1/query/dataset). It also lists all available packs, clearly distinguishing this data-access tool from sibling catalog/pack tools.

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?

Usage context is implied by the tool name and the pack list, but the description never explicitly says when to prefer this over get_catalog or get_pack. It also doesn't state prerequisites like needing a catalog first, so an agent must infer the selection logic.

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

All DaedalMap Distributed Manufacturing Locations toolsInspect
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TDQS

A4.2/5.0
Disambiguation5/5

Each tool serves a distinct purpose: get_catalog lists available packs, get_pack provides metadata for a specific pack, get_tool_help explains tool usage, and query_dataset fetches actual data. There is no overlap in functionality, and the descriptions clearly delineate when to use each.

Naming Consistency4/5

Three tools follow a clear 'get_X' verb-noun pattern (get_catalog, get_pack, get_tool_help), but the fourth, query_dataset, breaks this with a different verb. While still readable and predictable, the mixed use of 'get_' and 'query_' is a minor inconsistency.

Tool Count5/5

With only 4 tools, the server is well-scoped for its purpose: discovery (catalog), detailed metadata (pack), tool guidance (help), and data retrieval (query). Each tool is necessary and contributes to a cohesive workflow, fitting within the ideal 3-15 range.

Completeness5/5

The surface covers the full read-only lifecycle: discover packs (get_catalog), inspect a pack's metadata and usage (get_pack), understand tool-specific contracts (get_tool_help), and execute queries (query_dataset). No obvious gaps exist for the stated data access domain.

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