squiggle_get_ladder

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

No annotations are provided, so the description must carry the full burden of disclosing behavioral traits. It only states that each model gives its own projections, but it does not discuss data freshness, rate limits, authentication, error handling, or what happens with invalid inputs. The description lacks sufficient behavioral context.

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 concise sentences, front-loading the core purpose and adding a key detail about output. Every phrase earns its place with no redundancy or fluff.

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 complexity (3 parameters, multiple siblings, no output schema), the description could be more complete. It does not explain the return format, error behavior, or how to obtain model source IDs (though the schema hints at squiggle_get_sources). The distinction from squiggle_get_standings is implicit but not explicitly clarified, and no example usage is provided.

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 input schema covers all three parameters with descriptions (100% coverage), so the baseline is 3. The description adds minimal value beyond the schema, only tying the parameters together conceptually (e.g., 'by prediction model') and referencing the source parameter's purpose. No additional format, constraints, or usage details are provided.

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 verb ('Get'), the resource ('projected AFL ladder'), and the parameters ('given year and round, by prediction model'). It distinguishes from siblings like squiggle_get_standings by specifying 'projected,' and explains that each model outputs its own projected wins/mean rank.

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 when to use the tool (to get projected ladders) but provides no explicit guidance on when not to use it or how it compares to alternatives like squiggle_get_standings or squiggle_get_games. No exclusions or alternative tool names are mentioned.

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