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 real value with its provenance note that results come from a deterministic algorithm engine rather than an LLM, plus the shape of the return. It still says nothing about the operationally important behaviors for ORF finding, such as which reading frames/strands are scanned or whether a minimum ORF length applies.

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-loaded: purpose, then return value, then provenance note. The bracketed '【ORF 预测】' header largely restates the annotation title, which is mild waste, but nothing else is superfluous.

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 single-parameter tool with no output schema, the description does state what comes back (ORF list and positions), which covers the main gap. It omits the computational assumptions an agent would need to interpret or relay results correctly — genetic code table, strand coverage, minimum length — leaving it adequate but not complete.

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 required parameter with 100% schema description coverage ('核酸序列'), so the schema already carries the parameter burden and the baseline 3 applies. The description does not add format details such as FASTA vs raw string, allowed alphabet, or sequence-length limits.

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 and resource ('find open reading frames in a sequence') and states the return ('ORF list and positions'), so an agent knows exactly what the tool does. It does not differentiate itself from nearby sequence siblings such as act_sequence_translate or act_sequence_enzyme, which keeps it at 4 rather than 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 phrase 'when the user wants to find open reading frames in a sequence' implies the triggering intent clearly enough to route a request. However, it names no alternative tool and gives no exclusion criteria, so an agent comparing it against act_sequence_translate or act_sequence_plasmid has to infer the boundary itself.

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