run_diagnostic_rules

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

With no annotations, the description carries the burden. It discloses that rules requiring unavailable signals are skipped (not failed), explains confidence levels, and notes that findings include evidence. No side effects are mentioned but the tool likely is read-only.

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 two focused paragraphs. First paragraph states purpose and key features, second provides usage guidance. Every sentence adds value with no redundancy.

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 3 parameters and no output schema, the description explains the output structure (findings with evidence and confidence) and behavior (skipped rules). It covers interpretation needs well, though more detail on output fields would be beneficial.

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 33% (only rule_ids has a description). The description adds context for rule_ids (skipped behavior) but does not elaborate on start and end parameters beyond the time range concept. Baseline is lowered due to low coverage, but the added value is marginal for the required params.

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 verb ('Runs'), the resource ('domain diagnostic rule set'), and the output ('structured findings, each citing the specific data samples'). This distinguishes it from sibling tools like get_signal or list_available_signals.

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 guidance on interpreting low-confidence findings and checking the skipped list before concluding no problems exist. It does not explicitly compare to siblings but offers strong usage context.

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