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DataPulse

by io.github.r3dz4r
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Scope Reusable Data by Licence

find_by_licence
Read-onlyIdempotent

Return all datasets with the given licence, summarised. Use to enumerate what's available under a specific licence for compliance/reuse scoping. Use it to enumerate one licence; do not use it to discover by topic or inspect a dataset's citation context—use search_datasets or get_provenance instead. It reads published manifest data, so an empty list means no published dataset has the resolved licence; DataPulse is read-only, requires no API key, and the edge limits clients to roughly one request per second with a small burst, so pace or retry.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
licenceYesExact published licence name or supported alias, e.g. 'Creative Commons Attribution 4.0'; use search_datasets to discover licence values.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / licence / description
      Previous value: -"Exact licence name or supported alias, e.g. 'Creative Commons Attribution 4.0'."New value: +"Exact published licence name or supported alias, e.g. 'Creative Commons Attribution 4.0'; use search_datasets to discover licence values."
  2. Changed1 schema field changed
    • addedInput schema / properties / licence / examples
      Added value: +[
+  "Creative Commons Attribution 4.0",
+  "CC BY 4.0",
+  "OGL"
+]
  3. Changed2 schema fields changed
    • addedInput schema / properties / licence / description
      Added value: +"Exact licence name or supported alias, e.g. 'Creative Commons Attribution 4.0'."
    • addedInput schema / properties / licence / minLength
      Added value: +1
  4. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral context beyond annotations: it reads published manifest data, an empty list means no published dataset has the resolved licence, DataPulse is read-only and requires no API key, and the edge limits clients to roughly one request per second with a small burst. This is useful operational context that annotations do not provide.

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 compact and front-loaded: the core action and output are in the first sentence, followed by usage boundaries and operational notes. Every sentence earns its place, and there is no redundant restating of the tool name or schema fields.

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 single-parameter tool with a rich schema, clear annotations, and an output schema, the description covers the essential selection and invocation context: what it returns, when to use it, when not to, and operational constraints. Nothing an agent needs to call it correctly is missing.

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%, so the schema already documents the licence parameter with examples and a pointer to search_datasets for discovering values. The description adds the notion of 'resolved licence' and the exact-match/alias behavior, which slightly enriches the schema. Since the schema carries most of the burden, a 4 is appropriate rather than a 5.

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 states a specific verb ('Return all datasets with the given licence'), a clear resource (datasets by licence), and a summarised output. It also distinguishes itself from siblings by explicitly naming search_datasets and get_provenance as alternatives for different intents, so an agent can select it correctly without opening schemas.

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?

The description gives explicit when-to-use guidance ('enumerate what's available under a specific licence for compliance/reuse scoping') and explicit when-not-to-use guidance ('do not use it to discover by topic or inspect a dataset's citation context—use search_datasets or get_provenance instead'). It also clarifies the single-licence scope, leaving no ambiguity about alternatives.

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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