Tier Classification Assessment

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

Annotations already indicate read-only and idempotent behavior, so the bar is lower. The description adds useful context: it evaluates specific infrastructure aspects, identifies gaps, and returns target vs achieved tier, gap analysis with severity ratings, uptime expectations, and recommendations. This goes beyond the annotations without contradicting them.

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 well-structured with a clear overview, evaluation criteria, return value summary, parameter list, and examples. It is appropriately sized for a 10-parameter tool; every sentence adds value and the most important information (purpose) 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 complexity (10 params, no output schema), the description provides a complete picture: it states what the tool does, what it evaluates, what it returns, and includes two concrete examples. The annotations and full schema coverage cover safety and parameter details, so no critical context is missing.

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 baseline is 3. The description's Args list repeats parameter names and brief meanings, but the examples provide additional semantic value by showing how parameters like power_redundancy, cooling_redundancy, and distribution_paths are combined for realistic scenarios (e.g., 2N facility for Tier IV), which enhances understanding beyond the schema's dry definitions.

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 tool assesses a data center's Uptime Institute Tier classification based on infrastructure configuration, a specific verb+resource+scope. It distinguishes from sibling tools like dc_analyze_power_redundancy by covering multiple dimensions (power, cooling, distribution, maintainability, fault tolerance) rather than a single aspect.

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 explains what inputs are evaluated and mentions identifying gaps between current infrastructure and target tier, implying when to use it (when a tier classification assessment is needed). Examples show common queries like 'Does my N+1 facility qualify for Tier III?', but it does not explicitly discuss alternatives or exclusions relative to sibling tools.

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