misakanet_submit_usage

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

With no annotations provided, the description carries full behavioral disclosure. It states side effects ('currently returns a local placeholder report only'), error cases ('missing lesson_id'), auth ('none'), rate limits ('local stdio process only'), and output shape ('JSON with lesson_id, tool, outcome, and status'). It also flags the tool as '[Experimental]', giving the agent an honest expectation of reliability.

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 front-loaded with purpose, then organized into labeled sections: Input semantics, Output schema, Error cases, Side effects, Auth, Rate limits. Every sentence earns its place by disclosing a distinct behavioral or invocation detail. The structure makes it easy for an agent to parse.

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 no annotations and no output schema, the description is remarkably complete. It covers when to call the tool, required parameters, parameter semantics, expected response, failure mode, side effects, authentication requirements, and rate limits. For a 3-parameter experimental tool, nothing an agent needs to invoke or interpret the result is missing.

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 the baseline is 3. The description adds value by clarifying the intent of the 'tool' param ('tool names the calling client') and giving concrete outcome examples ('solved, partial, not-helpful, or another short status'). It also documents the expected output fields, which the schema does not. However, it repeats the 'lesson_id is required' schema constraint rather than adding new meaning.

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 opens with a specific verb and resource: 'Record that a public lesson helped with a problem.' This clearly identifies the action and object. It does not explicitly name a sibling, but the phrase 'submit usage feedback' meaningfully differs from the sibling list's read/search/write tools, so the purpose is distinguishable without opening the schema.

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 context: 'Use only after the user or calling agent explicitly chooses to submit usage feedback for a specific lesson.' This tells the agent exactly when the tool is appropriate. It does not mention when not to use it or point to alternatives, so it stops short of a full 5.

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