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Data Energystar

by io.github.pipeworx-io
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Query

query
Read-onlyIdempotent

Run a Socrata SoQL query against a ENERGY STAR Open Data dataset by resource_id (e.g. "83eb-xbyy"). Filter with where/select/group/order (SoQL clauses, without the leading $) plus limit/offset. Returns matching rows as JSON.

Input Schema

TableJSON 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. "83eb-xbyy" (from datasets).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / examples
      Previous value: -[
-  {
-    "limit": 100,
-    "resource_id": "83eb-xbyy",
-    "where": "year >= 2020"
-  }
-]New value: +[
+  {
+    "limit": 20,
+    "resource_id": "83eb-xbyy"
+  }
+]
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "limit": 100,
+    "resource_id": "83eb-xbyy",
+    "where": "year >= 2020"
+  }
+]
  3. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already convey read-only, idempotent, open-world, and non-destructive behavior. The description adds useful behavioral details beyond that: the SoQL syntax nuance ('without the leading $') and the return format ('Returns matching rows as JSON'). No contradiction with annotations exists.

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 a single, front-loaded sentence: the core action and target resource come first, followed by the clause list and return type. There is no filler, and the example resource_id is embedded naturally.

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?

With a fully documented schema and safety-bearing annotations, the description covers the essential invocation details. It includes return format and the key SoQL formatting rule, but it could be more complete by explicitly pointing to the datasets tool for finding resource_id or mentioning pagination limits.

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 each parameter in detail. The description mentions where/select/group/order and limit/offset, adding the '$' clarification, but does not materially expand on the schema's per-parameter explanations.

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 opens with a specific verb and resource: 'Run a Socrata SoQL query against a ENERGY STAR Open Data dataset by resource_id'. It clarifies the tool's job precisely and distinguishes it from sibling tools like datasets or metadata by emphasizing row-level querying and JSON output.

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 gives clear operational context: use SoQL clauses without the leading '$' plus limit/offset, and target a dataset by resource_id. However, it does not explicitly state when to prefer this tool over siblings such as datasets or metadata, nor does it mention any exclusions.

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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