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Openfema

by io.github.pipeworx-io
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Query Dataset

query_dataset
Read-onlyIdempotent

Generic OData query against any OpenFEMA dataset. Specify the entity name (and optionally version; defaults to the verified current version) plus OData params: filter, select, orderby, top, skip. Use list_datasets to see available entities/versions and the filter syntax. Returns { metadata, records }.

Input Schema

NameRequiredDescriptionDefault
topNoMax records ($top, default 50, max 1000).
skipNoRecords to skip ($skip) for paging.
entityYesDataset entity name, e.g. 'PublicAssistanceFundedProjectsDetails'.
filterNoOData $filter, e.g. "state eq 'TX' and fyDeclared eq 2023".
selectNoComma-separated $select fields, e.g. "disasterNumber,state,incidentType".
orderbyNoOData $orderby, e.g. 'declarationDate desc'.
versionNoPath version like 'v1'/'v2'/'v4'. Optional — defaults to the verified current version for known entities.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "entity": "DisasterDeclarationsSummaries",
+    "filter": "state eq 'FL' and fyDeclared eq 2023",
+    "select": "disasterNumber,state,incidentType,declarationDate"
+  },
+  {
+    "entity": "PublicAssistanceFundedProjectsDetails",
+    "orderby": "lastRefresh desc",
+    "top": 50
+  }
+]
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, non-destructive behavior. Description adds return format '{ metadata, records }' and version defaulting behavior, supplementing annotations effectively.

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 core function. No unnecessary details, each part earns its place.

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

Completeness4/5

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

Given 7 parameters, no output schema, and reliance on OData (external standard), the description provides essential context: what, how, where to get entities, and return shape. Could mention pagination or top/default limit (default 50 is in schema but not in description) but schema covers it.

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?

Input schema covers all 7 parameters with descriptions (100% coverage). Description adds value by clarifying that version is optional and defaults to current verified version, which is not in schema. Beyond that, it mostly restates OData params.

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?

Description uses precise verb 'query' and specifies resource 'any OpenFEMA dataset'. It distinguishes from sibling 'list_datasets' by referencing it for discovery, clarifying this tool is for actual data retrieval.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly directs users to list_datasets for available entities and filter syntax, providing clear complement. However, it does not explicitly exclude usage for datasets that may have dedicated tools (e.g., disaster_declarations), which could improve guidance.

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

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