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

Annotations already establish this as a read-only, closed-world computation, so the bar is lower. The description still adds real behavioral value by disclosing that the output is checked against the manufacturer's own datasheet limits and that the extension rate/denaturation come from the cataloged product — an agent knows the plan is constraint-validated, not free-form. It stops short of saying whether a limit violation raises an error, warning, or flag, which is the one behavior an agent would still want.

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?

A single sentence with two well-ordered clauses: the planning action first, the validation guarantee second. No filler, no restatement of the title, and the most decision-relevant qualifier ('NAMED enzyme') is front-loaded.

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?

With 12 parameters, nested _subject/_files objects, and an output schema present, the structured fields do most of the work, and return values need not be explained. The gap is workflow context: the description never says what inputs the tool expects to inherit from primer design or amplification, nor how the resulting programme should be used downstream. Adequate but thin for a tool of this parameter complexity.

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 100%, including detailed enum value descriptions for enzyme and polymerase, so the schema already carries the parameter burden. The description reinforces that enzyme selection drives extension rate and denaturation, but adds no syntax, format, or interaction detail beyond what the schema states. Baseline 3 is appropriate.

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 gives a specific verb and resource ('Plan the cycling programme for an amplicon') and adds a second concrete function: validating the reaction against the named manufacturer's published limits. The emphasis on 'a NAMED enzyme' implies a distinction from a generic preset, but no sibling tool (e.g. plan_master_mix, pcr_amplify) is named to anchor that contrast.

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?

Usage is implied: plan a thermocycler protocol once you have an amplicon, GC%, and Ta, and optionally a specific vendor enzyme. There is no explicit when-not guidance, no mention of prerequisites such as running design_primers or pcr_amplify first (that context exists only inside a parameter description), and no routing toward or away from neighbouring planning tools.

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