Get Leaderboard

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

With no annotations, the description carries the burden and does fairly well: it discloses the ranking protocol (within_session), sort order (desc by meanAccuracyPct), CI fields, and that 'updated'/'packFingerprint' annotate recency and provenance. It stops short of stating access/auth or rate characteristics, but for a read-only public benchmark that is minor.

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?

Front-loaded with the one-line purpose, then layered detail on protocol, sorting, and field meaning. Every sentence carries signal, though the field-by-field catalog is slightly dense and could be trimmed given an output schema exists.

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?

For a no-arg read tool with an output schema present, the description supplies enough context to call it correctly: what the leaderboard ranks, how rows are ordered, and how to reuse pipelineId downstream. Missing only explicit invocation context and access expectations.

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 tool takes zero parameters, so the baseline is 4. The description correctly adds no parameter detail because none exist, and instead spends its budget on return-field semantics, which is the right trade-off.

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?

States a specific resource ('Public benchmark leaderboard: pipeline rankings per dataset') with clear scope and per-dataset framing. It is confidently distinguishable from siblings like get_results or get_experiment, though it never explicitly names what it is not.

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?

Usage is only implied — the description assumes the agent knows this is the entry point for benchmark rankings. It offers a downstream chaining hint ('use pipelineId as the template id hint for get_template'), but no explicit when-to-use or when-not-to-use guidance versus other result-retrieval tools.

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