generate_cascode

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

With no annotations, the description carries the full burden. It discloses several behavioral traits: bias points computed for mid-supply output, bases driven directly by sources, no coupling caps/dividers, and the constraint 'Rc must exceed Re.' It also states the return is .CIR text. It does not mention error handling for invalid inputs, but coverage is good overall.

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 moderately long but well structured: a clear purpose statement, a short explanatory paragraph on the cascode's benefit, an Args list, and a return note. Each sentence provides relevant context, though the theory paragraph could be trimmed for a developer-focused AI without losing essential guidance.

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 moderate complexity (6 parameters, no annotations), the description covers the tool's purpose, parameter roles, key constraints, and return value. An output schema exists, so detailed return formatting is unnecessary. The description is sufficiently complete for an agent to select and invoke the tool correctly.

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%, yet the description compensates with an explicit Args section. It gives meaningful semantic details for all six parameters: rc/re ratio sets gain, vcc is supply voltage, source is AC drive added to bias, analysis is one of three modes, and output_node is the output label. This adds clear value beyond the schema.

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 clear verb+resource statement: 'Draw a .CIR cascode amplifier (common-emitter under common-base).' This precisely distinguishes the tool from sibling generator tools such as generate_emitter_follower and generate_differential_pair by naming the specific topology.

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 advantage of a cascode over a plain common-emitter ('Miller capacitance nearly vanishes and both output impedance and bandwidth rise'), giving clear context for when to select this tool. It does not explicitly list alternatives or when-not-to-use, but the reasoning is strong.

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