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

Annotations already mark the tool as read-only and non-destructive. The description adds context about interactivity, return of validation and share links (same as encode_graph_url), and a fallback for clients without UI support. It does not contradict annotations and provides meaningful behavioral detail beyond the structured fields, though it could clarify error handling or exact response structure if the output schema were absent.

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 fairly long but each sentence carries essential information: purpose, usage, parameter format, example, resource link, and fallback. It is front-loaded with the core purpose and structured logically. It could be slightly tightened, but the length is justified given the tool's complexity.

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 one parameter, annotations, and an output schema, the description covers all necessary aspects: when to use, how to format input, examples, validation behavior, and fallback handling. It also references an external syntax resource for advanced cases. Nothing an agent needs to invoke it correctly is missing.

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 already describes the equations array at 100% coverage, but the description adds significant value: it explains the complete graph must be passed, one equation per string, preserving unchanged rows, and provides a concrete slider syntax example. It also warns against joining rows with ';'. This goes well beyond the schema and compensates fully.

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 displays an interactive equation.io graph with specific features (editable equations, sliders, pan/zoom, 3D rotation). It distinguishes itself from encode_graph_url by noting it is for display and exploration, while encode_graph_url is for validation or link-only requests. The verb 'display' and resource 'graph' are precise, and the sibling differentiation is explicit.

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?

It explicitly states 'Use when the user asks to see or explore a graph' and directs link-only or validation requests to encode_graph_url. It also provides detailed usage instructions: passing the complete graph, preserving unchanged rows, and giving a slider example. This leaves no ambiguity about when to choose this tool over siblings.

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