predict

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

The description mentions proactive prediction based on context, recent activity, and learned patterns, and lists outputs. However, no details on side effects, authorization needs, or resource usage. Without annotations, the description should be more explicit.

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?

Two sentences: first defines purpose, second lists outputs. No redundant information, front-loaded with key actions.

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 covers what the tool does and what it returns. Given the complexity of a predictive AI tool and no output schema, more detail on output format or usage of context fields would improve completeness, but it is adequate.

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 has 100% coverage at the top level with a context object description, but nested fields lack descriptions. The tool description adds that context is used for prediction, but does not explain the role of each inner field (codebase, current_file, current_topics).

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 ('predicts') and resource ('memories'), and distinguishes the tool as proactive and predictive. Sibling tools include various memory operations but none specifically do proactive prediction.

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?

No explicit guidelines on when to use this tool versus alternatives like 'dream', 'intention', or 'search'. The description lacks context for appropriate use cases or exclusions.

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