feedback

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

Discloses that feedback is appended to a local log file (rag_storage/_feedback/feedback.jsonl) and notes it is never uploaded. Since annotations provide no behavioral hints (all false), the description fully informs about side effects and privacy.

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?

Single paragraph with clear structure: purpose, usage, privacy note, argument explanations. Every sentence adds value, no wasted words.

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 simplicity (3 string params, no nested objects), the description covers purpose, usage, behavior, and parameters. Output schema exists, so lack of return value explanation is fine.

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%, so baseline is 3. The description adds meaningful context by explaining each parameter's purpose in the feedback scenario, going beyond the schema's basic 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?

Clearly states the tool is for reporting failure to find needed information. Distinguishes from sibling search tools by specifying it's a feedback mechanism after exhausting search/deep_search/graph_query.

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?

Explicitly says 'Call this BEFORE giving up after exhausting search / deep_search / graph_query,' providing clear usage context. Lacks explicit when-not-to-use, but the situational guidance is strong.

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