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DaedalMap Disaster and Geospatial Data

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

A3.6/5.0
Behavior3/5

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

Annotations already mark the operation as read-only (readOnlyHint: true), and the description aligns by calling it a 'query'. It adds useful context beyond annotations by distinguishing free versus paid packs and mentioning the payment token (x402 Base USDC), which is a behavioral nuance about access costs, not just read-only safety.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is relatively long due to the enumerated pack list, but every sentence carries useful information: the purpose, the API contract, and the available free/paid packs. The main purpose is front-loaded, and the pack list serves as a quick reference, making the length justified.

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?

Given 8 parameters and no output schema, the description provides valuable context by listing all pack identifiers, which is essential for using pack_id. However, it does not describe the response format or any constraints of the 'same contract' beyond the mention, leaving the agent to infer return behavior. This is a notable gap given no output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

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 all parameters with descriptions. The description adds minor context by emphasizing the source_id/pack_id dichotomy, but it does not deepen parameter meaning beyond what's in the schema, so a baseline 3 is appropriate.

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 tool is a 'generic structured query' for 'direct source_id or pack_id access', which is a specific verb and resource. It distinguishes itself from the many specific sibling tools (e.g., get_earthquake_events) by being the generic query pathway, and even references the API contract for precision.

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 implies usage when you have a source_id or pack_id, and provides a list of valid packs, which gives context. However, it does not explicitly state when to prefer this over sibling tools or when not to use it, leaving some inference to the agent.

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

All DaedalMap Disaster and Geospatial Data toolsInspect
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TDQS

A3.9/5.0
Disambiguation4/5

Most tools have clearly distinct scopes with detailed 'Use this' guidance, but a few pairs like get_disaster_link_chain and get_disaster_links_for_event, or query_dataset versus the specialized get_* event tools, could cause momentary confusion. Overall, descriptions mitigate overlap well.

Naming Consistency4/5

The majority follow a consistent verb_noun pattern (check_, compare_, convert_, create_, estimate_, get_, list_, resolve_). Minor exceptions like loc_id_info and query_dataset are acceptable but break the pattern slightly.

Tool Count3/5

28 tools exceed the preferred range, but the broad domain spanning disasters, geospatial geometry, reference conversion, and export jobs justifies many of them. Still, the count feels heavy and might overwhelm agents.

Completeness5/5

The tool surface is remarkably comprehensive: discovery (catalog, pack, geometry catalog), resolution (point, reference, scope), geometry (check, get, compare), conversion (quote, create, status), and disaster events for multiple types. No critical dead ends for the stated domain.

Resources