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 the notion of a pass/fail scientific verdict but omits behavior beyond that — notably that all listed criteria are opt-in via parameters, so the sentence reads as if every check always runs. That is a mild transparency gap rather than a contradiction with the annotations.

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?

One front-loaded sentence states the verdict and then lists the four check families; nothing is wasted. The colon-separated enumeration is compact and scannable, though it stops just short of routing information.

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?

An output schema exists, so return values need not be explained, but with 16 parameters including the nested _subject/_files project context, the description never mentions the default behavior when no criteria are supplied, nor the record-versus-raw-sequence input modes. For a tool of this complexity that is adequate but leaves real gaps.

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 schema documentation is unusually rich (e.g. gc_window explaining that synthesis is rejected on a local GC peak rather than the mean). The description only names check categories generically ('protein unchanged', 'length/GC/CAI inside stated bounds') without mapping them to the specific options like preserve_protein_of, min_gc/max_gc, min_cai with cai_organism, or the require_frame/require_start/require_stop interaction. Baseline 3 is appropriate.

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 gives a specific verb and resource — 'Decide whether a sequence is scientifically admissible' — and enumerates the concrete checks (protein preservation, forbidden sites, frame, length/GC/CAI bounds). It does not differentiate the tool from overlapping siblings such as verify_construct, check_manufacturability, check_golden_gate_parts, or codon_optimality, so an agent must infer the boundary.

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?

There is no when-to-use guidance, no prerequisites, and no named alternative. With many sibling tools performing adjacent validation (check_manufacturability, verify_construct, audit_cds_annotations), the description leaves selection entirely to inference from the word 'admissible'.

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