suggest_plots

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

With no annotations provided, the description carries the full burden and does well. It discloses that profiling uses a reservoir sample of max_rows rows, that suggested calls reference the original source_id, and that sample_info indicates what was sampled. It also notes output size is small. This provides meaningful behavioral context beyond typical assumptions.

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 efficiently structured: it opens with a clear purpose, then adds behavioral details in short, crisp sentences. No redundant wording, though it could be slightly shortened without losing value.

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 purpose, internal logic, sampling behavior, and output characteristics. It references recommend_next for comparison and mentions sample_info. It does not explicitly explain how to choose between suggest_plots and recommend_next or other plotting tools, but this is a minor gap given the overall richness.

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 no descriptions for parameters (0% coverage), so the description must compensate. It clarifies max_rows (reservoir sample size) and hints (target/time columns), but max_suggestions is only named without explanation. source_id is self-explanatory. The description adds partial value but not complete compensation.

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: 'Recommend the most informative plots for a loaded source.' It specifies the resource (loaded source) and the action (recommend plots), and differentiates itself by referencing recommend_next and describing the internal inspection (column kinds, missingness, hints). This is a specific verb+resource+scope statement that distinguishes it from siblings.

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 usage by mentioning 'for a loaded source' and says it is 'similar to recommend_next,' but it does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or when-not-to-use guidance. The prerequisite (loaded source) is clear, but comparative guidance is absent.

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