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cloud.listSkills

List skills from the cloud library, filtered by AI type or source platform, for hierarchy-aware orchestration.

Instructions

List skills in the cloud library. Supports ai_type (skill|hook|steering|system-prompt|rule|agent|memory|spec|instructions|prompt) and source_platform (claude-code|cursor|kiro|amazon-q|copilot|windsurf|codex|agents|modelbound) filters. Each row includes ai_type, source_platform, source_path, and repo for hierarchy-aware orchestration. Requires MODELBOUND_API_KEY.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ai_typeNoFilter by AI file type (e.g. 'skill', 'hook', 'rule', 'system-prompt').
source_platformNoFilter by source platform (e.g. 'claude-code', 'cursor', 'kiro').
Behavior4/5

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

No annotations provided, but the description discloses that it lists skills, the returned fields (ai_type, source_platform, source_path, repo), and the API key requirement. It does not mention read-only or idempotency, but for a list operation this is sufficient.

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?

Three sentences, front-loaded with the main purpose, no wasted words. Each sentence adds meaningful information.

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?

Given it is a list tool with two optional parameters and no output schema, the description covers filters and output structure adequately. It does not mention pagination or error handling, but these are not critical for a simple list operation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description adds the specific enum values for ai_type and source_platform (e.g., 'skill|hook|...'), which are missing from the schema examples, providing valuable additional context.

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 clearly states the action ('list skills') and the resource ('cloud library'), and distinguishes from siblings like cloud.installMarketplaceSkill by being a listing operation.

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

Usage Guidelines3/5

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

The description mentions filters and the requirement for MODELBOUND_API_KEY, but does not provide explicit guidance on when to use this tool versus alternatives like skills.listLocal or cloud.search.

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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