Search a dataset catalog by free text or filters such as format, robot type, episode count, duration, and minimum health score to find matching embodied-AI datasets.
Query the dataset catalog by free text, format, robot type, episode count, duration or minimum health score.
| Name | Required | Description | Default |
|---|---|---|---|
| db | Yes | ||
| text | No | ||
| limit | No | ||
| format | No | ||
| min_score | No | ||
| robot_type | No | ||
| min_duration | No | ||
| min_episodes | No |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries full behavioral burden. It says nothing about read-only semantics, pagination behavior of 'limit', default ordering, result size, or what a result entry contains — only the filter dimensions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence, front-loaded with the verb and resource, zero filler. Every listed item maps to a real parameter and earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An eight-parameter search tool with no annotations, no output schema, and no schema descriptions needs more than a one-line field list. The required 'db' scope, 'limit' pagination semantics, and the shape of returned catalog entries are all undocumented.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate: it names six of the eight parameters (text, format, robot_type, min_episodes, min_duration, min_score). However, it omits the required 'db' parameter and 'limit' entirely, and phrases the numeric filters as bare nouns ('episode count', 'duration') leaving ambiguous whether they are minimum thresholds.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource ('Query the dataset catalog') and enumerates the filter dimensions it accepts, so the agent knows this is the search/filter entry point. It does not distinguish itself from siblings like catalog_index, catalog_stats, or list_formats, which are the likeliest confusion points.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No when-to-use, when-not-to-use, or alternative is given. An agent must infer from the name alone whether this or catalog_index / catalog_stats is correct for listing datasets, and there is no mention of prerequisites such as which 'db' to target.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.