Skip to main content
Glama

list_categories

Retrieve all categories assigned to a dataset, with an option to include soft-deleted entries.

Instructions

List categories for a dataset.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataset_idYesOwning dataset identifier.
include_deletedNoWhether soft-deleted categories are included.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okNo
dataYesContain ordered category records and their count.
Behavior2/5

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

With no annotations, the description carries the burden of disclosing behavioral traits. It only says 'List categories,' which implies a read operation but adds no context about default exclusion of soft-deleted items, permission needs, or pagination. The schema partially fills this gap, but the description itself contributes no extra behavioral transparency.

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, clear sentence with no filler words. It front-loads the action and resource, making it immediately understandable. It is appropriately sized for the tool's simplicity.

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?

The tool is simple, the schema covers all parameters, and an output schema exists, so return types are not the description's responsibility. The description is sufficient for the core operation, though it does not proactively distinguish from get_category or clarify the default filtering behavior. Minor gap but overall complete enough.

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% for both parameters, so the baseline is 3. The description does not add any additional meaning beyond what the schema already provides; it simply restates the tool's purpose without elaborating on parameter semantics.

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 uses the specific verb 'list' with the resource 'categories' and scopes it 'for a dataset,' clearly distinguishing it from sibling tools like get_category (single) or add_categories (creation). It also separates from list_datasets/list_images because the resource and scope are explicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given about when to use this tool versus alternatives such as get_category for a single category, or when to set include_deleted. The description merely states what it does without helping an agent choose among related category operations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ryan-minato/detection-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server