Get Organization Chart Summary

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

With no annotations, the description carries the behavioral burden. It discloses the output shape ('hierarchical view with minimal person data: uid, name, title, department, country') and the benefit ('reduced token usage'). It does not mention error handling or edge cases, but for a read-only operation this is adequate. It adds value beyond the schema by explaining the lightweight nature.

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 with no fluff. The first sentence states the purpose and core benefit, the second describes the output and the ideal use case. Everything earns its place, and the most important information is front-loaded.

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 the output schema exists and annotations are absent, the description adequately covers the tool's purpose, output fields, and use case. It doesn't mention pagination or limits on max_depth, but for a summary read tool this is a minor gap. Overall, an agent has enough information to call it correctly.

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%, so the baseline is 3. The description does not add any details about parameters beyond what the schema already provides (manager_id as identifier, max_depth with default). It mentions 'depth' only implicitly through the hierarchical view, but no additional semantic enrichment is given.

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 a specific verb+resource: 'Get lightweight organization chart for reduced token usage.' It explicitly distinguishes itself from the sibling get_organization_chart by emphasizing 'lightweight' and 'minimal person data,' making its purpose unambiguous.

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?

It provides a clear context for use: 'Ideal for large organization charts where token usage is a concern.' This implies when to prefer it over the full chart, though it does not name the alternative tool explicitly or state when not to use it. The condition is direct enough for an agent to infer the right choice.

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