suggest_type

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

Without annotations, the description carries full burden and excels: it declares read-only, stateless, idempotent, no side effects, authentication requirements (none for basic, key for Pro), rate limits (10/day free, unlimited Pro), error handling (structured errors), and data privacy. This comprehensive disclosure exceeds typical requirements.

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 labeled sections but excessively verbose. The 'Behavioral Transparency' section repeats information from earlier 'Behavior' section. Approximately 50% of the text could be trimmed without losing meaning, making it less efficient for an AI agent to parse.

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 presence of an output schema (not shown), the description appropriately avoids detailing return values. It covers purpose, usage, parameters, and extensive behavioral details. Minor gap: rate limits and authentication details are split between sections. Still, it provides a complete picture for a tool of moderate complexity.

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 'Args' section provides minimal descriptions: 'description (str): The description to analyze or process' and 'api_key (str): The api key to analyze or process.' Given 0% schema description coverage, these are insufficient—they don't clarify expected format, how the key is used, or that Pro requires an environment variable (not the parameter). The parameter meaning is ambiguous.

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: 'Suggest the best conventional commit type for a change description with confidence scoring.' This distinctively identifies the tool's purpose and differentiates it from siblings like analyze_diff, generate_commit_message, and validate_conventional, which cover other aspects of commit analysis.

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 includes 'When to use' and 'When NOT to use' sections, providing context: use for structured analysis/classification, not for real-time production decisions without human review. However, it does not explicitly contrast with siblings, leaving some ambiguity about when to prefer this over analyze_diff or validate_conventional.

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