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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds meaningful context beyond annotations by clarifying that this returns knowledge documents as tool output for clients unable to access MCP resources. No hidden mutation, auth, or side-effect concerns are left undisclosed.

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?

A single, front-loaded sentence achieves clarity and includes the key usage directive. Every part earns its place; no redundant phrases or clutter.

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?

The description covers what the tool returns for whom, and when to invoke it ('before interpreting any Space Monkey metrics'). Since annotations are already rich and the only parameter is fully documented in the schema, nothing essential is missing for correct invocation.

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 fully documents the optional 'topic' parameter, its enum values, and the default behavior of fetching all documents. The description adds no extra parameter-level meaning, but with ~100% schema coverage the baseline of 3 is appropriate.

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 uses a specific verb ('Returns') and clearly identifies the resource being returned: Space Monkey's MCP knowledge documents. It also enumerates the document types (analyst preamble, metric guardrails, OpenAPI schema URL), which distinguishes this from typical data-fetching sibling tools like sm_get_account or sm_get_insights.

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 states when to use the tool: for clients that cannot read MCP resourcesandar to consult this before interpreting any Space Monkey metrics. It does not explicitly name sibling alternatives or when not to use the tool, but the use-case instruction is concrete enough for an agent to route appropriately.

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