veto_learning_stats

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

Annotations already indicate readOnlyHint=true, so the description doesn't need to reiterate safety. It adds context about the dashboard contents but doesn't disclose any additional behavioral traits like rate limits or result size.

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?

Two sentences, front-loaded with the object being returned (dashboard), followed by usage. Every word adds value; no fluff.

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 read-only stats tool with three boolean parameters and no output schema, the description covers the return contents and purpose. It misses default parameter values and potential performance considerations, but overall it is sufficiently complete.

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 adequate parameter descriptions. The tool description lists the dashboard components but doesn't explicitly tie each parameter to its effect, though the parameter names and schema descriptions suffice. No additional value beyond schema.

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 returns a 'self-learning router dashboard' with specific contents (tier distribution, per-agent stats, threshold adjustments, council insights), distinguishing it from sibling tools like veto_council_debate or veto_learning_apply.

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 phrase 'Use to understand how the router is performing and where to improve' provides clear context, but no explicit alternatives or when-not-to-use guidance is given, which would be helpful given the large sibling set.

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