squiggle: Get tips

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

Annotations already indicate readOnlyHint, openWorldHint, and idempotentHint. The description adds value by detailing the output fields (margin, confidence, correctness), which enhances the agent's understanding of what the tool returns without contradicting the annotations.

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 two sentences with no wasted words. It is front-loaded with the primary action ('Get game-level tips/predictions') and efficiently conveys the key points.

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?

While the description explains the output, it lacks guidance on how to use parameters together (e.g., year+round to get all tips for a round) and data volume considerations (many tips if game omitted). Given the openWorldHint, completeness could be better. No output schema exists, so the description carries this burden.

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?

Schema coverage is 100% with descriptions for all four parameters. The description hints at the 'source' parameter ('one or all models') but does not add substantial new meaning beyond the schema. Baseline 3 is appropriate.

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 retrieves game-level tips/predictions from Squiggle models, specifying the content (margin, confidence, correctness). It effectively distinguishes from sibling tools like squiggle_get_games and squiggle_get_sources by focusing on predictions.

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 filtering by source with 'one or all models' but does not explicitly state when to use this tool versus alternatives. For example, it could note to use squiggle_get_sources for model metadata or squiggle_get_games for raw game data. No exclusion criteria are provided.

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