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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so safety is covered. The description adds genuinely useful context that results come from a real algorithm engine rather than LLM generation, plus the shape of the return (subtyping + prognosis). It does not say how missing inputs are handled even though all four parameters are optional.

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?

Very short and front-loaded: purpose, trigger, return value, then a trust qualifier, in that order. Nothing is redundant, though the bracketed title repeat and the engine claim are slightly promotional rather than operational.

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 correctly carries the return-value burden by naming the two outputs. However, for a tool where zero parameters are required, it never indicates the minimum viable input set or whether partial data still yields a subtype, leaving a real operational gap.

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%, so each parameter is already documented, and the description restates three of them (TILs/CD8/PD-L1) without adding units, valid ranges, or weighting. It says nothing about cancer_type, which is the one parameter whose role is least obvious.

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?

Names a specific resource and action: tumor microenvironment analysis driven by TILs/CD8/PD-L1 inputs, with the outputs ('微环境分型与预后提示') stated up front. An agent can distinguish it from adjacent siblings like act_ihc_score or act_mif_phenotype, though it does not explicitly say how it differs from them.

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 a clear trigger condition: use when the user has TILs/CD8/PD-L1 data and wants a microenvironment assessment. It does not name an alternative tool or state when NOT to use it, so there is no explicit routing logic for ambiguous cases such as users with only IHC scoring needs.

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