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

Annotations already indicate a non-readonly, non-destructive write operation. The description adds valuable behavioral context: validation is performed first (same checks as validate_program), invalid programs are refused with fix hints, and the output is a markdown preview plus a shareable URL. This goes beyond the annotations and informs the agent of side effects and outcomes.

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 dense but well-organized: it leads with the core purpose, then a bolded usage directive, then behavioral notes, then output details. It avoids filler and front-loads the most important information. It is longer than minimal but earns its length with specific, non-redundant content.

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 tool's complexity (nested program object, validation rules, publishing side effects) and the existence of a detailed output schema, the description covers the essentials: purpose, usage rule, validation behavior, and output format. It also points to a guide for authoring rules. No critical information for an agent to call it correctly is missing, though it could mention the allowInvalid parameter more explicitly (but that's in the schema).

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 coverage is 100%, with detailed descriptions for both parameters (program and allowInvalid). The description does not add parameter-specific semantics beyond referencing validation and output, which is more about tool behavior. It mentions the program must be valid by default, but that's also implied by the allowInvalid default. Baseline 3 is appropriate since the schema already documents the parameters thoroughly.

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 states a specific verb and resource ('Render a multi-step parallel schedule as a live timeline') and clarifies scope ('Call this for ANY schedule you produce — imported, catalog match, or built freehand'). It also implicitly distinguishes from siblings like validate_program (validation is done inside) and preview_timeline (publishes a live timeline, not just a preview).

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 gives an explicit 'when to use' directive ('Call this for ANY schedule you produce') and a rule of thumb ('A schedule belongs in a visualization, never in prose'). It mentions that invalid programs are refused, implying you don't need a separate validation call, but it doesn't explicitly name alternatives or when NOT to use it. Still, the guidance is strong and actionable.

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