list_presetsList available question sets to pass as a preset, avoiding the need to write your own questions.
Question sets you can pass as preset instead of writing your own.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.2.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and a closed-world scope, so the safety profile is covered. The description adds the useful linkage that values are passed as `preset`, but says nothing about the size or shape of the returned list beyond what the output schema presumably provides.
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 with no filler, front-loading the resource and its purpose. It is arguably too terse to be maximally useful, but nothing in it is wasteful.
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?
Because an output schema exists, the description need not explain return values. Still, for a discovery tool in a set of nine decision-related siblings, the description does not say enough to route the agent confidently here versus describe_questions.
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 takes no parameters, so there is nothing for the description to disambiguate; baseline 4 applies. No parameter meaning is missing.
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 names the resource (curated question sets) and its role as a `preset` value, so an agent understands it enumerates usable presets. However it never states the verb 'list' explicitly and does not distinguish itself from the sibling `describe_questions`, which an agent could easily confuse it with.
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 'instead of writing your own' implies usage context – use this to discover presets rather than author your own question set. But there is no explicit when-to-use vs alternatives guidance, and no mention of how the returned presets feed into other tools such as decide.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.