predictive_prevention

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

No annotations are provided. The description mentions analyzing patterns to predict failures but does not disclose behavioral traits such as whether it is read-only, what side effects exist, or any resource 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 extremely concise, consisting of two lines with a clear trigger and purpose. It uses an emoji for visual cues and directly states the key action. 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 simplicity (one optional parameter) and the presence of an output schema, the description provides adequate context. Minor gaps remain in usage guidelines and behavioral transparency, but overall it is fairly complete.

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 coverage is 0%, meaning no parameter descriptions in the schema. The description adds 'Number of predictions to generate' for the limit parameter, which provides basic semantics beyond the schema's type and default.

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: to see predicted failures based on pattern analysis. It mentions specific analysis elements (anti-patterns, quality trends, missed detections). However, it does not differentiate from sibling tools like 'predict' or 'check_anti_patterns'.

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 'TRIGGER' prefix implies a specific usage scenario, but there is no explicit guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites.

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