compare_self

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

The description discloses the read-only nature (returns assessment without modification) and explains both input modes (codename fetches from board, text computes locally). Annotations already provide readOnlyHint=true, but the description adds details on what is returned and the fact that no data is mutated.

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 concise at 5 sentences, front-loaded with the primary purpose. Every sentence adds value: purpose, input modes, return values, usage examples. 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 moderate complexity (two optional parameters, output schema present, multiple return fields), the description covers all necessary aspects: what it does, when to use it, how inputs work, what outputs to expect. It references siblings indirectly by its specific focus.

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 descriptions for both parameters. The description adds value by clarifying that 'text' is for 'raw token pillars' with examples like 'ccusage JSON' and notes case-insensitivity for 'codename'. This goes beyond the schema descriptions, earning a 4.

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 the tool compares an operator's metrics against board averages and power-user archetypes, returning a behavioral assessment. It also lists specific return values. This distinguishes it from siblings like 'compare_operators' (compares two operators) and 'describe_power_user' (describes characteristics).

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 explicitly specifies when to use the tool: when users ask 'how do I measure up to other AI users?', 'am I a power user?', or 'compare me to others'. It also mentions the intent is COMPARE_SELF, providing clear context for invocation.

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