annotate_regulatory_context

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

With no annotations, the description carries the full burden and does so well: it discloses that live inference runs via score_variant using SDK-recommended scorers, the variant types supported (SNV, indel, MNV), that the response carries `source: live`, and that it makes no pathogenic/benign call. This is rich behavioral context an agent cannot get from structured fields.

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, front-loaded paragraphs: what it predicts, how it runs, and the disclaimers. Efficient overall, though the final disclaimer paragraph is somewhat long and repeats the non-clinical framing already implied by the first paragraph.

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?

With no output schema, the description usefully explains what the result contains (source marker, scores and calibrated quantiles) and what it deliberately omits (pathogenicity calls). It doesn't detail the per-modality result structure, but for an annotation tool with full schema coverage the coverage is adequate.

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 each parameter (chromosome, position, ref, alt, tissue_type) is already documented in the schema with patterns and defaults. The description adds no syntax or semantics beyond the schema, so the baseline of 3 applies.

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 (annotate/predict) and resource (variant effects across all regulatory modalities), enumerating the modalities covered: accessibility, histone marks, TF binding, CAGE, RNA-seq, splice sites, polyadenylation and contact maps. The phrase 'across every regulatory modality at once' implicitly differentiates it from single-modality siblings like predict_splice_impact or predict_tf_binding_impact.

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?

Explicitly frames the intended use ('research prioritization, not clinical classifications') and states it does not label the variant, which steers an agent away from it when a pathogenic/benign call is needed (assess_pathogenicity). It does not, however, name a specific sibling alternative or give explicit when-not conditions beyond the clinical boundary.

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