list_prompts
List all available prompts.
Returns JSON with prompt metadata including name, description, and optional arguments.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
List all available prompts.
Returns JSON with prompt metadata including name, description, and optional arguments.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
Output schema / descriptionAdded value: +"Generic wrapper for non-object return types."Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds that the result is JSON metadata, which is useful context. No contradictions are present.
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?
The description is brief, direct, and free of unnecessary detail. Two sentences convey the action and the return format efficiently.
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 simple no-argument list operation, the description is sufficiently complete. It names the return type and the key fields, though it does not specify ordering or pagination, which are not critical here.
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 the parameter semantics are trivially satisfied. The description does not need to elaborate on inputs.
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 clearly states the tool's purpose: to list all prompts and return their metadata. It is distinguishable from the sibling get_prompt tool, which retrieves a specific prompt.
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 usage is implied by 'List all prompts', but there is no explicit guidance about when to prefer this over get_prompt or other listing tools. It is adequate but not fully explicit.
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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