list_capabilitiesLists native Provider, model, reasoning, agent preset, and permission preset options so you can reference exact names without guessing.
List native Provider/model/reasoning, agent preset, and permission preset options without guessing names.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.2.6Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only, idempotent, and non-destructive behavior, so the bar for extra disclosure is lower. The description adds that the tool returns canonical option names rather than guesses, which is useful, but it does not describe output format, ordering, or any environment-specific behavior.
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?
A single sentence that front-loads the verb and object, lists the option categories compactly, and closes with a meaningful behavioral qualifier. Every word adds value and nothing is redundant.
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?
For a zero-parameter, read-only discovery tool, the description is complete: it names exactly what the agent will learn and gives no ambiguous invocation requirements. No output schema is present, but the description adequately conveys the return concept — available option names.
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?
The tool has zero parameters, so the input schema is intentionally empty and there is no parameter burden to document. Baseline for zero-parameter tools is 4; the description adds relevant semantic context by naming the categories of values the tool exposes.
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?
The description states a specific verb ('List'), resource (native Provider/model/reasoning, agent preset, and permission preset options), and a clear purpose ('without guessing names'). It distinguishes this tool from sibling list tools like list_services, list_workspaces, and list_runs by naming the exact option categories it covers.
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?
The phrase 'without guessing names' implies this tool should be used when the agent needs authoritative option values before configuring or running something. It provides clear context for when to call it, though it does not explicitly name alternative tools or state when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.