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

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=false, so safety is covered. The description adds something genuinely useful beyond that: the result comes from a real algorithm engine rather than LLM generation, which tells the agent to trust it as deterministic computation. It stops short of describing what the plan contains, how long it takes, or what the engine assumes.

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 short line with the topic front-loaded in brackets and the return value stated at the end; nothing is padded. The mixed bracket/parenthesis formatting is slightly noisy but costs no comprehension.

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 no output schema, the description must convey what comes back, and it does only at the label level ('实验设计方案'). For a design tool with a free-text constraints parameter, an agent still lacks guidance on plan granularity or expected inputs, though the fixed annotations reduce the burden.

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% and there are only two parameters (target, constraints), so the schema already carries parameter meaning. The description mentions neither parameter and gives no examples of what a useful 'constraints' string looks like, so it adds nothing on this dimension — baseline 3 applies.

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 bracketed header names a technique and domain (Bayesian adaptive design, qPCR) and says the output is an experiment design plan, so the rough purpose is legible. But 'digital twin PCR' is unexplained jargon and nothing distinguishes this from the many design-adjacent siblings (act_primer_design, act_qpcr_ddct, act_design_guide, act_design_sample_size).

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 offers a trigger condition — the user wants to do qPCR experiment design — which implies when to reach for it. It never says when NOT to use it, nor names any alternative among the crowded design/qPCR sibling set, so an agent choosing between act_primer_design and this tool gets no routing help.

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