snapshot_repo_create

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It implies a write operation ('创建') but doesn't specify whether this requires admin permissions, if it's idempotent, what happens on conflicts (e.g., duplicate names), or error conditions. The examples hint at settings but don't explain behavioral outcomes like storage implications or rate limits. This is inadequate for a mutation tool with zero annotation coverage.

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 structured with a purpose statement, parameter list, and examples, which is logical. However, it includes redundant formatting (extra whitespace) and could be more front-loaded; the examples are detailed but might bury essential usage info. It's moderately concise but not optimally streamlined for quick comprehension.

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 the complexity (a mutation tool with nested objects and no output schema) and lack of annotations, the description is incomplete. It covers parameters well but misses critical behavioral details (e.g., permissions, idempotency, error handling) and doesn't explain the return value or success/failure indicators. For a tool that creates resources in a system like Elasticsearch, this leaves significant gaps for an AI agent.

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 schema description coverage is 0%, so the description must compensate. It explicitly lists all three parameters (name, type, settings) with brief explanations and provides concrete examples for 'fs' and 's3' types, adding meaningful context beyond the bare schema. However, it doesn't fully document all possible 'type' values or 'settings' structures, leaving some ambiguity. Given the low schema coverage, this is strong but not exhaustive.

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 verb ('创建' meaning 'create') and resource ('快照仓库' meaning 'snapshot repository'), making the purpose unambiguous. It distinguishes from sibling tools like 'snapshot_repo_delete' and 'snapshot_repo_get' by specifying creation. However, it doesn't explicitly differentiate from other repository-related tools beyond the name, keeping it at 4 rather than 5.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing specific permissions or existing infrastructure), when not to use it, or how it relates to sibling tools like 'snapshot_create' or 'snapshot_repo_verify'. This lack of contextual guidance limits its utility for an AI agent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.