interactive_feedback

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

With no annotations provided, the description carries the full burden. It details the iterative feedback loop, requiring the tool to be called repeatedly, adjusting behavior based on feedback, and providing a summary and project directory. However, it does not specify behavior on timeout or empty feedback, leaving some edge-case ambiguity.

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 well-structured with a clear list of usage rules and is front-loaded with the purpose. However, rules 1–4 are repetitive, all emphasizing the need for repeated calls, which could be condensed. It is informative but not maximally concise.

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 when to use, how often, what to pass, and when to stop, making it quite complete for an interactive tool. An output schema exists, so return values are covered. The main gaps are the lack of behavior on timeout or empty feedback, which slightly detracts from completeness.

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 already provides descriptions for all three parameters (100% coverage), so baseline is 3. The description adds extra meaning by explaining that 'summary' reflects the AI's completed work and that 'project_directory' helps the user see what was done. This justifies a score above 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 clearly states it is an 'Interactive feedback collection tool for LLM agents,' specifying its core function. It does not explicitly distinguish from sibling tools, but the only sibling (get_system_info) is unrelated, so differentiation is less critical. The purpose is clear and actionable.

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 usage rules are explicit and comprehensive: it mandates calling the tool during any process, repeatedly unless termination instructions are given, and only stopping when the user indicates 'end'. This provides unambiguous guidance on when and how to use it, effectively covering alternatives by ruling out not using it.

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