get_fix_suggestions

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'Get suggestions' but doesn't describe what the suggestions include (e.g., code fixes, explanations), how they are formatted, whether this is a read-only operation, or any limitations (e.g., rate limits, dependencies on prior analysis). For a tool with zero annotation coverage, this leaves significant gaps in understanding its 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?

The description is a single, clear sentence that efficiently conveys the tool's purpose without waste. It is front-loaded with the key action ('Get suggestions') and avoids redundancy. Every word earns its place, making it highly concise and well-structured.

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 (simple, no parameters) and lack of annotations and output schema, the description is adequate but incomplete. It states what the tool does but doesn't cover behavioral aspects like what the suggestions entail or how they are returned. For a tool with no structured data to rely on, it should provide more context to be fully helpful.

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?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate. Baseline is 4 for zero parameters, as there's nothing to compensate for, and the description doesn't introduce unnecessary complexity.

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 action ('Get suggestions') and the target ('for fixing issues found in the last analysis operation'), which is specific and actionable. It distinguishes from siblings like 'analyze_js_file' or 'get_analysis_report' by focusing on post-analysis fixes rather than analysis or reporting. However, it doesn't explicitly mention the resource type (e.g., JavaScript files), which keeps it from a perfect score.

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 implies usage context ('in the last analysis operation'), suggesting this tool should be used after an analysis operation. However, it doesn't explicitly state when to use it versus alternatives like 'get_analysis_report' or provide exclusions (e.g., whether it works without a prior analysis). The guidance is implied but lacks explicit alternatives or prerequisites.

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