feedback

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

With no annotations, the description must disclose behavior fully. It mentions the interactive nature and timeout, but does not specify side effects (e.g., if feedback is stored), error handling, or what happens on timeout. Some behavioral transparency is provided but not complete.

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 headers and numbered rules, but it is verbose, repeating 'call this tool' multiple times. It could be more concise while retaining clarity.

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 complexity and the presence of an output schema, the description covers the feedback loop comprehensively: when and how to use, parameter roles, and termination conditions. Minor gaps like timeout behavior are acceptable.

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 coverage is 100% with parameter descriptions in Chinese. The description adds usage context for 'message' (e.g., providing explanations) but does not significantly enhance semantics beyond the schema. Baseline score 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 clearly states it is an 'Interactive feedback collection tool for LLM agents', specifying the verb (collect) and resource (feedback). It distinguishes from the sibling tool 'get_system_info' by focusing on feedback interaction.

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 explicit usage rules: when to call (during any process/task), how often (repeatedly), when to stop (explicit 'end' or 'no more interaction'), and alternatives for termination. This is a model of clear guidance.

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