report_tokens

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

The description labels the action as 'Mutating' and explains that the value is stored server-side. However, it lacks detail on side effects, idempotency, or permission requirements. With no annotations, the description carries the full burden but is only moderately transparent.

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 with 3-4 sentences, front-loaded with the mutation indicator. Every sentence adds value, though it could be slightly tighter.

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?

For a simple reporting tool with two parameters and no output schema, the description provides sufficient context about purpose, usage, and parameter semantics (except connection_id). The inclusion of server-side storage and visibility via get_match_telemetry adds 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 description explains the 'tokens' parameter as a positive integer for the token count, which adds meaning beyond the schema. However, 'connection_id' is not described, and since schema coverage is 0%, the description only partially compensates for the missing parameter documentation.

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 reports LLM token consumption for cost tracking. The description is specific about what is reported and why, and it distinguishes itself from sibling tools like report_issue by focusing on tokens.

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 notes that the tool is called by the client harness after each turn and is not typically called by the agent itself. This provides clear guidance on when to use it, though it does not mention alternatives or when not to use it beyond self.

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