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 only 'RETURNS: 差异 peak' and says nothing about the statistical method, thresholds, replicate requirements, or failure modes. With annotations carrying the safety burden, a 3 is fair, but the behavioral value added is thin.

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?

The pipe-delimited header is front-loaded with the purpose, then USE WHEN, ALIASES, and RETURNS, so scanning is easy and there is no filler prose. The bilingual duplication and a long alias list cost a little density but are defensible for retrieval matching.

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?

There is a single, fully documented parameter and no output schema, so the description is the only place to explain return values — yet it gives just '差异 peak' with no indication of the output fields, thresholds, or how many peaks come back. Complete enough to trigger a call, but not enough to interpret the result.

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 the data_json description is unusually detailed about matrix/rows/cols/groups/p_values/log2fc shape and the required-field behavior, so the schema does the heavy lifting. The tool description adds no meaning beyond the schema, which is the baseline 3 case.

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 analysis (differential accessibility on ATAC-seq counts) rather than restating the tool name, so an agent knows this takes ATAC count data and produces differential peaks. It does not explicitly contrast with close siblings such as differential_expression or chip_peak_calling, so the distinction is inferable rather than stated.

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?

The 'USE WHEN: differential open regions from ATAC-seq counts' clause gives a concrete triggering condition, including the required input type (counts) and the goal (differential open regions). There are no exclusion conditions or named alternatives, so an agent must still infer when to pick differential_expression or chip_peak_calling instead.

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