Credit Optimizer v5

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

No annotations are provided, so the description carries the full burden. It states the tool returns an 'optimal strategy with model recommendation and directives,' which implies a read-only, advisory function, but doesn't disclose behavioral traits like error handling, performance characteristics, or any constraints (e.g., rate limits, authentication needs). The description adds minimal context beyond the basic purpose.

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 appropriately sized and front-loaded, with the purpose stated first, followed by brief sections for args and returns. There's minimal waste, though the structure could be slightly more streamlined (e.g., integrating the args list into the main text).

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 moderate complexity (1 parameter, no annotations, but with an output schema), the description is minimally adequate. It covers the purpose and parameter semantics but lacks usage guidelines and behavioral transparency. The presence of an output schema means the description doesn't need to detail return values, but overall completeness is limited by gaps in guidance and context.

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 schema description coverage is 0%, so the description must compensate. It adds meaning by listing the allowed values for 'task_type' (qa, code, research, content, data_analysis, media, automation), which clarifies the parameter beyond the schema's generic string type. However, it doesn't explain the semantics of these task types or provide examples, leaving some ambiguity.

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: 'Get the optimal strategy for a specific task type.' It specifies the verb ('Get') and resource ('optimal strategy'), but doesn't explicitly differentiate from sibling tools like 'analyze_prompt' or 'get_golden_rules', which might offer related but distinct functionality.

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 no guidance on when to use this tool versus its siblings ('analyze_prompt', 'get_golden_rules'). It mentions task types but doesn't specify contexts, prerequisites, or exclusions for usage, leaving the agent to infer appropriate scenarios.

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