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Glama

Data Gov In

by io.github.pipeworx-io
OverviewAdmin

Resource Meta

resource_meta
Read-onlyIdempotent

Fetch the schema/metadata for a data.gov.in resource by resourceId: title, publishing org, sector, last-updated time, and the list of fields (each with name, id, type). Use this to discover the filterable/sortable field ids before calling resource_data. The resourceId is the UUID from the dataset's page on data.gov.in.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
_apiKeyYesdata.gov.in API key
resourceIdYesThe dataset resource UUID from its data.gov.in page (e.g. "9ef84268-d588-465a-a308-a864a43d0070").

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "_apiKey": "your-data-gov-in-api-key",
+    "resourceId": "9ef84268-d588-465a-a308-a864a43d0070"
+  }
+]
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations cover safety (readOnlyHint, idempotentHint, non-destructive). The description adds behavioral context beyond annotations by specifying the return contents (metadata fields, field name/id/type) and the purpose of the resourceId. It does not contradict 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?

Two sentences, leading with the action and resource, then providing the key use case. No filler or redundant content; 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 the tool's simplicity, the description fully explains the return structure (title, org, sector, last-updated, field list with name/id/type) and its purpose. Missing details like error handling or rate limits are minor for a read-only metadata fetch, especially with strong annotations.

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 covers 100% of parameters with descriptions and examples, so the baseline is 3. The description reinforces that resourceId is a UUID from the dataset page, which adds slight context, but no new parameter semantics beyond what the schema already provides.

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's function: 'Fetch the schema/metadata for a data.gov.in resource by resourceId'. It lists the specific contents (title, org, sector, last-updated, fields), and explicitly distinguishes it from the sibling tool resource_data by saying 'before calling resource_data'.

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?

Provides direct usage guidance: 'Use this to discover the filterable/sortable field ids before calling resource_data.' This tells the agent when to use this tool and how it relates to the likely alternative (resource_data), including the sequential dependency.

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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