Record an installation of a skill from skills-hub.ai. If the caller belongs to an organization, the org's install policy is enforced and a blocked install returns an error explaining the policy.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Skill slug to install (e.g. 'code-review') | |
| platform | No | Target platform (default 'CLAUDE_CODE'; e.g. 'CURSOR', 'CODEX_CLI', 'WINDSURF') |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses that installation enforces organizational policy and returns an error if blocked. However, it does not mention idempotency, response format, authentication needs, or other behavioral traits like whether duplicate installations are prevented.
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?
Two concise sentences with no redundant information. The first sentence states the action and source, and the second adds a critical condition. Front-loaded and efficient.
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?
Given no output schema, the description covers the main action and a key behavioral aspect (policy enforcement). It does not describe the return value or prerequisites, but for a tool with only 2 simple parameters and clear siblings, it is fairly complete. Could be improved by mentioning success/failure indications.
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?
Schema description coverage is 100%, with clear parameter descriptions (e.g., 'Skill slug to install' and 'Target platform with default'). The tool description adds overall context but does not enhance parameter semantics beyond what the schema already provides, achieving the baseline.
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?
Description clearly states the verb 'Record an installation' and the resource 'a skill from skills-hub.ai'. It also adds the organizational policy enforcement detail. The tool's purpose is distinct from siblings like get_skill_detail or search_skills, which are read-only.
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 description provides context on when to use (to install a skill) and notes that organizational policy may block the install. However, it lacks explicit exclusionary guidance or alternative tool references, though the purpose is sufficiently clear.
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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