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

Annotations already mark the tool as read-only and non-destructive. The description adds meaningful context beyond that: it reveals the testing process, the default provider (Groq), that no api_key is needed with the server key, and the option to supply api_key + model for a custom provider, plus the PASS/FIX/BLOCK verdict behavior.

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?

Three sentences, front-loaded with purpose, followed by process, output, and provider details. No fluff; each sentence earns its place. The only minor issue is the default-model mismatch with the schema, but structurally it is concise and well-organized.

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?

The description explains the core workflow, return verdict, and auth model, and an output schema exists to cover return details. It does not describe scenario_count default or enumeration constraints, but the schema covers those. The description is complete enough for a moderate-complexity read-only tool, though the model default inconsistency is a clarity gap.

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 covers all four parameters at 100%, so baseline is 3. The description adds provider-switching context but lacks extra param nuance. However, it contains a default-model contradiction: the description says 'Groq llama-3.3-70b' while the schema's model param says 'Defaults to openai/gpt-oss-20b (Groq, server key)', undermining the reliability of the added info.

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?

Description opens with a specific verb+resource: 'Validate a SKILL.md definition'. It details the process (auto-generating trigger-positive/negative scenarios, running each through the model with the skill injected as a system prompt) and distinguishes itself from generic test tools by focusing on SKILL.md files for Cursor/GitHub Copilot/Windsurf and scoring trigger accuracy + step adherence.

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 intended use case is explicit—validating a SKILL.md definition—though it does not name alternative tools or provide when-not-to-use guidance. The domain targeting (Cursor / GitHub Copilot / Windsurf) gives clear context for when this tool is appropriate.

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