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

Annotations already declare readOnlyHint=true, openWorldHint=false and destructiveHint=false, so the safety profile is supplied structurally. The description's only behavioral addition is 'RETURNS: 修饰位点预测', which largely restates the tool's own purpose and says nothing about output fields, scoring, thresholds or how predictions should be interpreted.

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 definition is short and front-loads purpose followed by USE WHEN, ALIASES and RETURNS, which is easy to scan. The ALIASES list is largely keyword padding for retrieval rather than information an agent needs in order to invoke the tool correctly.

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?

For a two-parameter, read-only prediction tool with full schema coverage this is close to sufficient, but with no output schema the vague 'RETURNS: 修饰位点预测' leaves the agent guessing what the result actually contains (site positions, confidence scores, supported modification types). A brief note on the result shape would close the 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 description coverage is 100%, with both 'sequence' and 'modifications' documented, so the schema carries the parameter burden and 3 is the baseline. The description adds nothing beyond the schema, since the phosphorylation/glycosylation examples it mentions already appear in the modifications field description.

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 title line names a specific verb+resource ('Post-translational modification prediction'), and 'USE WHEN: predict phosphorylation / glycosylation and other PTM sites' pins down the exact operation, which is distinguishable from sibling protein tools such as protein_physchem, protein_digest and protein_enrichment. It does not explicitly name a sibling it is not, so it falls short of a 5.

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' clause gives a clear trigger context (predicting PTM sites, with phosphorylation and glycosylation called out). There are no exclusions or pointers to alternative tools for adjacent tasks like physchem properties or enrichment, so it is clear context without when-not guidance.

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