plot_bar

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

With no annotations, the description carries the burden of behavioral disclosure. It mentions the tool plots value counts for top N categories and supports vertical/horizontal orientation, but does not disclose whether it modifies data, displays vs. saves the plot, or how df_name/save_path are used. Some useful details are present, but significant gaps remain.

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 concise and front-loaded: one sentence stating the core functionality, followed by usage rationale, and a clear example. No filler or redundant text.

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 the tool's main purpose and provides a usage example, but with no output schema and 5 parameters, it omits details about df_name and save_path and does not clarify the return value (e.g., shows a plot object). It is minimally complete for a simple plotting tool but has clear gaps.

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 description coverage is 0%, so the description must compensate. The example `plot_bar(column="CargoType", top_n=10, orientation="horizontal")` clarifies the meaning of column, top_n, and orientation. However, df_name and save_path are not explained, leaving ambiguity for those parameters.

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: "Bar plot of value counts (top N categories)" with a specific verb and resource. It distinguishes from sibling plot tools by focusing on categorical value counts, making it easy to select for categorical distribution analysis.

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 gives useful context: "Understand categorical distributions during EDA. Reveals rare categories for potential grouping and dominant categories for stratified sampling." This indicates when to use the tool, but it does not explicitly name alternatives or exclusions (e.g., when not to use it).

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