maid_get_schema

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

No annotations are provided, so the description must disclose behavior. It states the return type (SchemaResult with manifest schema) but does not explicitly confirm it is read-only or safe. However, the tool's purpose implies no side effects, so the description is adequate but not thorough.

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 well-structured with clear sections for usage, key information, and tips. It is slightly longer than necessary but every sentence adds useful context. Front-loading with the main purpose is effective.

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 tool's simplicity (no parameters, output schema exists), the description covers all necessary aspects: when to use, what the schema contains, and tips. It is complete for an agent to understand and invoke the tool correctly.

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 input schema has zero parameters, and the description provides no parameter details (none needed). According to the baseline rule for 0 params, the score is 4. The description adds value by explaining the return content and context.

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 retrieves the MAID manifest JSON schema, with a specific verb and resource. It distinguishes itself from siblings by explaining its role in understanding manifest structure before other operations like validation or creation.

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 explicitly lists when to use the tool in Phase 2 (Planning), debugging, and learning contexts. Although it doesn't state when not to use it, the context is clear and aligns with typical use cases for a schema retrieval tool.

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