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

With no annotations, the description carries the full burden. It doesn't disclose whether the tool is read-only, whether there are side effects, or any limitations. The description is purely functional with no behavioral context.

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 a single sentence, which is concise but under-specified. It's not verbose, but it lacks detail needed for effective use. It's appropriately front-loaded but a bit too sparse.

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?

Even with an output schema present, the description doesn't explain return types or formatting. It provides no context about the structure of the time-series output or how to interpret results. For a tool with three parameters and significant output, the description is incomplete.

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 describes all parameters with 100% coverage, so the baseline is 3. The description adds no additional meaning beyond what the schema provides, so it stays at 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?

The description states a specific action (time-series sentiment analysis) and resource (feedback sources), but it doesn't distinguish itself from sibling tools like get_pain_points or search_feedback. It's clear enough but lacks differentiation, making it average.

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?

There is no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, exclusions, or typical use cases, leaving the agent to infer usage from the name alone.

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