trace_rule_execution

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

No annotations provided, so description carries full burden. It discloses that it fetches current employee data, checks rule conditions, and shows match results with reasons. Implicitly indicates read-only behavior (no mention of modifications). Could add more about side effects or data freshness.

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?

Four sentences, no wasted words. Front-loaded with action and purpose, then explains mechanics, then provides use case. Every sentence adds value.

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?

Output schema exists, so return structure is covered. Description explains what the tool does and its debugging value. Missing details on prerequisites (e.g., rule configuration must exist) and any limitations. Adequate for a debugging tool with good sibling context.

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 only 50%, with optional parameters (data_center, auth credentials) lacking descriptions. The description does not clarify these parameters' roles, relying on the schema which is incomplete. Added parameter semantics are minimal.

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?

Specifies verb 'trace' and resource 'business rules for an employee event'. Distinguishes from sibling 'list_business_rules' by explaining it evaluates conditions against live data, not just listing. Includes debugging context.

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 frames as debugging 'why did this field get this value?', but does not specify when not to use or compare directly to other siblings. Context is clear enough for an agent to infer usage scenario.

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