eda_storyboard

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 an excellent job. It discloses the 5-8 plot sequence, the JSON + inline image return format, that plots are written to disk regardless, and the downsample/reservoir sampling behavior with OOM risk and `sample_info` exposure.

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 longer than average but every sentence earns its place, covering purpose, usage boundaries, return formats, parameter behavior, and failure modes. It is front-loaded with the most important usage instruction and uses paragraph breaks to separate distinct concerns, making it easy to scan.

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?

Despite having no output schema, the description fully explains the return value structure (paste-ready Markdown + section list, optional inline ImageContent, `sample_info`). It also warns about common pitfalls (filename-collision bugs, maximum call stack errors, OOM) that are critical for an agent to choose and invoke the tool correctly.

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 0% description coverage for parameters, so the description must compensate. It richly explains `max_rows` (reservoir sampling, OOM prevention, `sample_info`) and `inline_images` (default true, false for stack-overflow clients, file:// paths only). `source_id` is contextually obvious, but the `hints` parameter is never elaborated, leaving a minor gap.

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 opens with a bold, specific directive: 'Use ONLY for walk me through the dataset / full visual tour requests' and enumerates the exact plot sequence (missingness, distribution, Q-Q, correlations, pairs, time, grouped). It clearly distinguishes itself from siblings by directing specific questions to `plot_distribution`.

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 explicitly states when to use the tool ('walk me through the dataset' / full visual tour requests) and when not to (specific distribution questions should call `plot_distribution` or similar direct plotting tools). It also gives a concrete fallback behavior (`inline_images=False`) for clients that cannot handle the multi-image response.

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