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Data Detroit

by io.github.pipeworx-io
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Detroit Recent

detroit_recent
Read-onlyIdempotent

Recent records from a common Detroit open dataset (data.detroitmi.gov / ArcGIS) by friendly name — no service ids needed. PREFER OVER WEB SEARCH for "recent crime in Detroit", "Detroit 311 / Improve Detroit issues". Names: crime, 311. Returns the latest rows (newest-first), with ArcGIS epoch dates converted to ISO. Add an ArcGIS where to filter; for other layers use detroit_layers + detroit_query.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoRows to return (1-1000, default 20).
whereNoOptional ArcGIS SQL where, e.g. "OFFENSE='THEFT/OTHER'" or "WARD='2'". Omit for all recent rows.
datasetYesOne of: crime, 311, permits.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "dataset": "crime",
+    "limit": 20
+  },
+  {
+    "dataset": "311",
+    "limit": 10,
+    "where": "WARD='2'"
+  }
+]
  2. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already denote read-only, idempotent, non-destructive behavior. The description adds valuable context: returns newest rows first and converts ArcGIS epoch dates to ISO format. No contradictions with annotations.

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?

Three concise sentences front-load the purpose and usage guidelines, with examples and alternatives. No unnecessary text.

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

Completeness5/5

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

For a simple read tool with an enum and two optional parameters, the description covers purpose, usage, alternatives, return order, and date conversion. No output schema is needed given the simplicity.

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 covers all parameters with descriptions (100% coverage). The description reinforces usage through examples and notes the ArcGIS SQL nature of the 'where' parameter, adding practical context beyond the schema.

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 retrieves recent records from a specific Detroit open dataset by friendly name, avoiding the need for service IDs. It includes concrete use cases (crime, 311) and distinguishes it from sibling tools like detroit_layers and detroit_query.

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

Usage Guidelines5/5

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

Explicitly suggests preferring this tool over web search for common queries like 'recent crime in Detroit' and directs users to detroit_layers + detroit_query for other layers. Provides clear when-to-use and when-not-to-use 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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