get_decision_metadata_distribution

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

With no annotations, the description carries the burden. It discloses that the tool costs DAC and uses 'Observe' to imply a safe, read-only operation. However, it does not detail return structure, pagination, or rate limits, so it provides only partial behavioral transparency.

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 a single sentence that front-loads the purpose, specifies the fields, and includes the cost caveat. Every word earns its place with zero 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 simple read tool with one parameter and no output schema, the description is largely complete: it states the fields, scope (branch-1 decisions), and cost. It lacks details about response formatting or edge cases, but these are not critical for understanding the tool's core function.

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 description coverage is 100% (auth_token described. The description adds no additional parameter semantics beyond the schema, which is fully self-explanatory. Baseline of 3 is appropriate because the schema carries all parameter information.

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 uses the specific verb 'Observe' to indicate viewing, identifies the resource as 'decision metadata distribution', and lists the exact fields broken down (decision_class, target_class, decision_trigger, human_involvement). It distinguishes from the sibling get_self_classification_distribution by scoping to 'branch-1 decisions'.

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 clear context: use this tool to see a breakdown of decision metadata from branch-1 decisions. It does not explicitly name alternatives or exclusions, but the scope is well-defined. Mentioning 'Costs DAC' adds important usage guidance about the tool's cost.

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