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LumabyteCo

Clarifyprompt-MCP

list_platforms

Lists available AI platforms for a specific category, including custom registered platforms, to help users select the right platform for prompt optimization.

Instructions

List available platforms for a category, including custom registered platforms.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryYesCategory to list platforms for
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what the tool does but doesn't describe behavioral traits such as whether it's read-only, if it requires authentication, rate limits, or what the output format looks like (e.g., list structure, pagination). For a tool with zero annotation coverage, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose. It avoids unnecessary words and gets straight to the point. However, it could be slightly more structured by explicitly separating the main action from additional details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what information is returned (e.g., platform names, IDs, custom status) or any behavioral constraints. For a tool with no structured output documentation, the description should provide more context about the result format and usage implications.

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?

The input schema has 100% description coverage, with the 'category' parameter fully documented via enum and description. The description adds no additional parameter semantics beyond what the schema provides (e.g., it doesn't explain the meaning of categories like 'chat' or 'image'). Baseline score of 3 is appropriate as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'List' and the resource 'available platforms for a category', and specifies the inclusion of 'custom registered platforms'. It distinguishes from siblings like 'list_categories' by focusing on platforms within a category rather than categories themselves. However, it doesn't explicitly differentiate from other platform-related tools like 'register_platform' or 'update_platform' in terms of purpose.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose 'list_platforms' over 'list_categories' or 'list_modes', nor does it specify prerequisites or exclusions. The context is implied (listing platforms for a category) but lacks explicit usage instructions.

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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