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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds valuable behavioral context: 'Pure pattern-matching', 'No inference, no external calls', and the behavior with no inputs ('recommended config and a 'unknown' verdict'). This goes beyond the annotations and fully discloses the tool's non-invasive 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?

The description is front-loaded with the main action, then explains behavior and parameter optionality in a compact, scannable structure. Each sentence adds value: purpose, method/limitations, return value, and input flexibility. No wasted words.

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 tool's complexity (6 optional params, output schema present), the description is complete. It explains what the tool does, how it behaves (pattern-matching), what it returns (critical issues, non-fatal warnings, recommended baseline config), and edge-case behavior (no inputs). The output schema handles return details, so no further elaboration is needed.

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%, with each parameter having a meaningful description (e.g., 'Empty = skip this check'). The tool-level description adds only a general note that all parameters are optional, not per-parameter details. Baseline 3 is appropriate since the schema carries the parameter semantics.

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's purpose: 'Validate an SGLang configuration for NVIDIA DGX Spark (GB10/SM121A).' The verb 'Validate' plus the specific resource (SGLang config on specific hardware) distinguishes it from the sibling blog tools (get_article, list_tags, search_blog), which are unrelated.

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 for when to use: to validate a config against known failure modes. It explicitly explains constraints ('Pure pattern-matching... No inference, no external calls') and parameter optionality ('supply only what you have'). However, it does not explicitly state when not to use it or name an alternative, though no alternative is relevant among siblings.

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