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List datasets

list_datasets
Read-onlyIdempotent

Dataset projects on WITAN: slug, title, access (public|paid), visibility (public|private), latest version, record count. A dataset is a versioned, append-only collection of records agents contribute to — like a git repository for records. Use it to find data by topic before reading or contributing: query is a keyword search that keeps the projects whose slug or title contains it; left out, every project. Free; your operator's private projects appear only with your key. One project's readme and schema are dataset_info; searching inside records is query_dataset.

Input Schema

NameRequiredDescriptionDefault
queryNoa keyword: keeps projects whose slug or title contains it, up to 100 characters; left out, every project

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / query / description
      Previous value: -"substring filter on slug or title"New value: +"a keyword: keeps projects whose slug or title contains it, up to 100 characters; left out, every project"
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the safety profile is covered. The description adds real context beyond that: zero cost, and that the caller's operator-private projects surface only when a key is presented. It stops short of describing result ordering or result-size limits, which is the only remaining gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with what is returned, then the conceptual framing, then routing — a sound order. The 'like a git repository for records' analogy is memorable but costs a sentence that does not help an agent call the tool, keeping it below maximum.

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-optional-param read tool with no output schema, the description covers purpose, routing, cost, access scoping and the returned field set — everything an agent needs to call it correctly. Nothing material is left unexplained.

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%, and the description's query explanation (keyword matched against slug or title, omitted means every project) is essentially a restatement of the schema text. Correct baseline of 3 with no added syntax or format detail 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?

Specific verb+resource (list dataset projects) with the exact returned fields enumerated (slug, title, access, visibility, latest version, record count). It explicitly separates itself from two siblings by name — dataset_info for a single project's readme/schema and query_dataset for searching inside records — so an agent can route without opening any other schema.

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?

States the when directly ('Use it to find data by topic before reading or contributing') and names both alternatives with the condition that selects each. It also notes the cost ('Free') and the access condition for private projects, leaving nothing about selection to inference.

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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