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Data Kingcounty

by io.github.pipeworx-io
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Query

query
Read-onlyIdempotent

Run a Socrata SoQL query against a King County Open Data dataset by resource_id (e.g. "j56h-zgnm"). Filter with where/select/group/order (SoQL clauses, without the leading $) plus limit/offset. Returns matching rows as JSON.

Input Schema

NameRequiredDescriptionDefault
groupNoSoQL $group column(s).
limitNoMax rows (default Socrata 1000).
orderNoSoQL $order, e.g. "date DESC".
whereNoSoQL $where filter, e.g. "year >= 2020 AND status = 'Active'".
offsetNoPagination offset.
selectNoSoQL $select, e.g. "name, count(*) AS n".
resource_idYesDataset id, e.g. "j56h-zgnm" (from datasets).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / examples
      Previous value: -[
-  {
-    "limit": 50,
-    "resource_id": "j56h-zgnm",
-    "where": "year >= 2020"
-  },
-  {
-    "group": "category",
-    "order": "total DESC",
-    "resource_id": "j56h-zgnm",
-    "select": "category, count(*) AS total"
-  }
-]New value: +[
+  {
+    "limit": 20,
+    "resource_id": "j56h-zgnm"
+  },
+  {
+    "limit": 20,
+    "resource_id": "j56h-zgnm",
+    "select": "book_of_arrest_number"
+  }
+]
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "limit": 50,
+    "resource_id": "j56h-zgnm",
+    "where": "year >= 2020"
+  },
+  {
+    "group": "category",
+    "order": "total DESC",
+    "resource_id": "j56h-zgnm",
+    "select": "category, count(*) AS total"
+  }
+]
  3. First observed

TDQS

A4.2/5.0
Behavior3/5

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

Annotations already cover read-only and idempotent hints, so the bar is lower. The description adds context about the datasets being from King County Open Data and the syntax for SoQL clauses (without $), which is useful beyond the schema. However, it doesn't disclose potential rate limits, response size behavior, or error handling, which could be relevant.

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 two sentences, with the primary purpose front-loaded. It includes a concrete example of resource_id and clarifies key syntax without fluff. Every sentence 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 that the tool has 7 parameters but only 1 required, and no output schema, the description covers the essential context: what it queries, how to specify parameters, and the default limit. It doesn't explain return value shape, but that might be standard JSON as mentioned. It is fairly complete for a read-only query tool.

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 description coverage is 100%, and the schema already explains each parameter with examples. The description adds value by clarifying the SoQL syntax (e.g., 'without the leading $') and mentioning the default limit of 1000, which enriches the meaning of 'limit'. Given the high schema coverage, the baseline is 3, and the description earns a 4.

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 that this tool runs Socrata SoQL queries against King County Open Data datasets, identified by resource_id. It specifies the primary action (query) and the resource, and it distinguishes itself from related tools like 'datasets' and 'metadata' that likely handle dataset discovery rather than querying.

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?

The description explains the general usage context (run queries on datasets) and mentions 'datasets' as a source for resource_id, implying a prerequisite step. It does not explicitly mention alternatives or when not to use it, but the context is clear enough for an agent to decide.

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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