interactive_feedback

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It reveals mandatory call patterns, stopping conditions, reaction to non-empty feedback, and [NEW TASK] handling—going far beyond a simple tool summary.

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 longer than typical but well-organized with sections and numbered rules. Some repetition exists (e.g., 'must call this tool' repeated across rules), but the structure makes the behavioral mandates clear and easy to follow.

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 tool has no output schema, but the description explicitly states the return type (list of TextContent and MCPImage). It fully covers usage rules, argument purposes, default timeout, and edge cases like [NEW TASK], making it self-contained for an agent.

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 100%, so the baseline is 3. The description adds some context—e.g., project_directory is for user context and summary is for user review—but largely restates information already present in the input schema defaults and descriptions.

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 identifies the tool as an 'Interactive feedback collection tool for LLM agents,' specifying its resource (user feedback) and purpose. It is sharply distinguished from the sibling tool get_system_info, which is unrelated.

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?

Contains explicit USAGE RULES with numbered steps detailing when to call the tool (during any process, after feedback, until termination), when to stop ('end' or 'no more interaction needed'), and how to handle [NEW TASK] prefixes. This is exemplary guidance.

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