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

With no annotations, the description carries the full burden. It discloses the key non-obvious behavior: polling until completion, bounded waiting, and typical cold-start latency. It does not cover timeout/error behavior or explicitly confirm read-only semantics, but the central behavioral trait is transparent.

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 short sentences deliver the essential behavior and usage condition with no filler. The most important information is front-loaded.

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 fully captures the core workflow: call detect_ai_text, receive 'processing', then poll here. It omits the response shape and explicit timeout/error semantics, but for a simple fetch-and-poll tool with an explicit usage condition, the essential context is present.

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 0%, so the description must compensate. It clarifies uuid as the lookup key and 'bounded' polling hints at timeout behavior, but it never explicitly links max_wait_seconds to the bound or explains what happens when the wait is exceeded.

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 states a specific verb and resource ('Fetch a text detection by UUID') and adds polling behavior that differentiates it from initiation tools like detect_ai_text. An agent can clearly identify this as the follow-up retrieval tool.

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?

It explicitly says when to use it: after detect_ai_text returned status 'processing', with the cold-start context adding nuance. It does not specify when not to use it or name alternatives such as get_detection, so it stops short of a full exclusion-based guideline.

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