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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds genuine context by stating the computation is run by a real algorithm engine rather than generated by an LLM, but it says nothing about input expectations, runtime, or what the peak list contains beyond its name.

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?

Two short clauses, front-loaded with the bracketed domain tag, with zero filler. It is efficient, though the extreme brevity leaves no room for the operational detail an agent would need.

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?

Peak calling is a non-trivial domain operation, and the only return-value guidance is 'peak list' with no output schema to fall back on. More importantly, the input schema describes a generic feature-by-sample matrix with groups/p-values, which does not obviously match ChIP-seq peak calling inputs (aligned reads/controls), and the description never bridges that 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?

There is a single parameter and schema description coverage is 100%; the schema itself explains data_json in detail (matrix/rows/cols/groups/p_values and the required-field rejection). The description adds no parameter meaning at all, so the baseline 3 for fully documented schemas 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 description names a specific verb+resource pair (ChIP-seq peak calling) and states the return artefact (a peak list), which is enough to distinguish it from neighbouring omics tools such as act_atac_diff, act_rnaseq_deg and act_enrich. It stops short of explicitly contrasting with those siblings, so it is clear but not maximally differentiated.

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?

"用户有 ChIP-seq 要做 peak calling" implies the trigger condition (user brings ChIP-seq data and needs peaks called), but nothing is said about prerequisites (what form the input must take, whether input/control samples are needed) or when a sibling tool would be the better choice. Usage is inferable rather than stated.

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