predict_splice_impact

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

With no annotations, the description carries the full burden and does well: it discloses that inference runs live via score_variant, marks the result with source: live, defines the accepted variant classes, and warns that outputs are model predictions with no pathogenic/benign call. It omits runtime cost or failure modes, which keeps it short of a 5.

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?

Three short blocks, led by the output scope, then the inference behavior, then the caveat — front-loaded and each sentence earns its place. Slightly redundant restatement of the non-clinical caveat keeps it from a 5.

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 no output schema, but the description compensates by enumerating the returned elements (splice sites, usage, junctions, gene and junction per result) and flagging source: live. An agent has enough to invoke it correctly, though the shape of returned scores/quantiles is only sketched.

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%, so position, ref, alt, chromosome, and tissue_type are fully documented in the schema already. The description adds no syntax or format guidance beyond that, so a 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?

States a specific verb-effect and resource: predicted splicing effects of a variant, enumerating the outputs (splice sites, splice site usage, splice junctions). It is clearly distinguishable from generic siblings like predict_variant_effect or predict_tf_binding_impact without opening a schema.

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?

It gives clear scope (single-nucleotide variants, indels, multi-nucleotide variants) and implies the intended use case of research prioritization rather than clinical classification, which implicitly routes away from assess_pathogenicity. However, it never explicitly names when to prefer a sibling such as predict_variant_effect for a broader effect profile.

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