add_math_expression_node

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

No annotations are provided, so the description carries the full disclosure burden. It does disclose key behaviors: creates a collapsed graph, variables become input pins, result is the Return Value output pin. But it omits mutation implications (it modifies a blueprint), any connection/compile side effects, and failure behavior. With zero annotation coverage, more disclosure would be warranted.

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?

Well-structured with a clear purpose statement, an Args block, and an example. The purpose is front-loaded. Some redundancy exists — the 'From Ch. 15:' and 'Example from the book:' citations add context but are slightly extraneous; the example itself is genuinely useful for illustrating the variable-to-pin conversion.

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 moderate-complexity mutation tool (3 params, 1 required), the description covers all parameters, gives a worked example, and points to a knowledge base reference. An output schema exists to cover return values. It is fairly complete, though it could mention whether the added node is auto-connected or left floating, and any blueprint-save implications.

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, and it does. The Args section documents all three parameters: blueprint_name (Blueprint to add the node to), expression (with the variable-to-pin behavior), and node_position ([X, Y] graph position). This adds real meaning beyond the bare schema, especially for expression and node_position which have no schema descriptions.

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?

States a specific verb+resource ('Add a Math Expression node') and explains its distinctive semantics: it creates a collapsed graph from a formula string, with variables becoming input pins and a Return Value output pin. This clearly differentiates it from the many math-related siblings like add_math_node and add_arithmetic_operator_node.

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 explains the tool's behavior well (collapsed graph, variable-to-pin mapping) which implies when to use it, and includes a concrete example. However, it never explicitly distinguishes when to choose this over the math-node siblings (add_math_node, add_arithmetic_operator_node, add_abs_node), so an agent gets no explicit exclusion or alternative guidance.

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