predict_expression_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 fairly well: it discloses that inference is live (via score_variant with SDK-recommended scorers), that the response is marked `source: live`, and that no pathogenic/benign call is made. Missing are cost/latency implications of live inference and any failure-mode notes, keeping 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?

The output scope is front-loaded in the first line, followed by computational behavior and the research-use disclaimer. It is tight for the number of concepts covered, though the disclaimer sentence is somewhat verbose.

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 does describe the return content (per-gene/tissue log fold change, CAGE, calibrated quantiles, source marker), and with no annotations it covers the research-only caveat. It is largely complete for a prediction tool, though the absence of return-shape or failure detail is a minor 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%, so all five parameters are already documented in the schema, making 3 the baseline. The description's mention of 'per gene and tissue' loosely reinforces the tissue_type filter but adds no syntax or format detail beyond what the schema provides.

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 ('predicted gene expression effects of a variant') and pins the output modalities (RNA-seq log fold change per gene/tissue, CAGE), which lets an agent distinguish it from modality-specific siblings like predict_splice_impact or predict_tf_binding_impact. It does not explicitly contrast itself with the near-neighbor predict_variant_effect, leaving some ambiguity.

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 states the applicable variant classes (SNV, indel, MNV) and that it runs live inference, which is useful scoping. But it offers no when-to-use/when-not guidance relative to alternatives such as predict_tissue_specific or assess_pathogenicity, so routing is only implied.

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