plot_model_map

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the tool 'displays it to the user' and 'Returns whether the operation was successful,' which gives some context about user interaction and return values. However, it lacks critical details: whether this is a read-only operation, what happens if the model doesn't exist, what format the map takes, whether it requires specific permissions, or any side effects. For a visualization tool with zero annotation coverage, this is insufficient.

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 appropriately concise with two sentences that directly address core functionality. The first sentence covers the main action and technology, while the second addresses return value. There's no fluff or redundant information, though it could be slightly more structured with parameter details.

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?

Given the complexity (visualization tool with user display), lack of annotations, 0% schema coverage, and no output schema, the description is incomplete. It doesn't explain the parameter, error conditions, what 'successful' means concretely, or how the map is presented. For a tool that likely involves graphics generation and user interaction, more context is needed.

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 input schema has 1 parameter with 0% description coverage, so the description must compensate. It doesn't mention the 'model_name' parameter at all—no explanation of what it represents, format requirements, or where valid names come from (e.g., from list_models). The description adds no parameter semantics beyond what the bare schema provides.

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: 'Creates an interactive map of the SWMM model using Plotly and displays it to the user.' This specifies the verb ('creates'), resource ('map of the SWMM model'), technology ('Plotly'), and user-facing behavior ('displays it to the user'). It distinguishes from siblings like plot_output_data or plot_rainfall by focusing on model structure visualization rather than output data or rainfall plots.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing model), when-not-to-use scenarios, or comparisons with similar tools like get_model_info or other plotting tools. The agent must infer usage from the purpose alone.

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