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

Adds substantial behavior beyond the annotations: questions freeze once the first wave fields (an irreversible constraint), scorer requires a metricId (cross-parameter dependency), and the tool may return a needs_confirmation envelope. These are exactly the traits an agent needs and none are in the structured fields.

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?

Front-loaded with the core purpose, then the immutability warning, then the optional binding and launch alternative. Dense with parentheticals and em-dashes but nearly every clause carries decision-relevant information; slightly long for the payload.

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 12-parameter mutation with no output schema, the description covers the two highest-risk facts (question immutability, needs_confirmation flow) and the metric binding. It leaves the success/return shape and scheduling edge cases unstated, but the schema covers the rest adequately.

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 92%, so the schema does the heavy lifting; the description nonetheless adds the non-obvious rule that a `scorer` needs a `metricId` and clarifies what a scorer does. It does not explain interval/dayOfWeek/scheduleTime interactions beyond what the schema already says.

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 and resource ('Creates a research program that fields the SAME instrument on a schedule'), with concrete examples (brand tracking, weekly pulse) and the key distinction that each wave is an ordinary study. This clearly separates it from prism_series_launch_wave and prism_series_update.

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?

Gives clear usage context: freeze the questions with the user first, optionally bind a Ledger metric + score rule. It names the sibling alternative for on-demand launches ('Waves launch on schedule, or on demand with prism_series_launch_wave'), though it does not state explicit exclusions for when not to create a series.

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