plot_heatmap

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

With no annotations provided, the description carries the full burden and discloses useful behavioral details: it uses pandas .corr() with the same formula as correlation_matrix, returns null r for constant columns, omits p-values/corrections, and accepts inline_data in two shapes. It does not explicitly state the return format or whether the plot is returned as an image/path, so it stops short of a 5.

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 compact and front-loaded with the core purpose, followed by formula, limitations, and inline-data details in a readable layout. The 'tool 23, core implementation' phrasing is mildly redundant, but the overall structure earns its place.

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 tool with no annotations and no output schema, the description covers core behavior and inline-data formats well, but it omits file_path semantics and the exact return/visualization contract. The external SPEC reference helps but pushes required details outside the description.

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. It does explain inline_data thoroughly: mutually exclusive with file_path, supports records arrays or header/rows objects, and references SPEC section 12 for limits. However, it gives no semantic detail about file_path beyond its existence, and the limits are deferred to an external document rather than stated.

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 specific verb and resource: plotting a pairwise Pearson correlation heatmap for all numeric columns, with r values in cells. It also distinguishes itself from correlation_matrix by noting the shared formula but explicitly no p-values or corrections, which disambiguates it from the main sibling.

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 clear context for when it applies (numeric-column correlation heatmap) and explicitly states what it does not do: p-values and corrections, citing a division of labor with 'tool 4'. However, the reference to 'tool 4' is not resolved by name, and there is no explicit guidance for choosing this over other plotting siblings such as plot_scatter or plot_histogram.

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