predict_allele_specific_effects

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

With no annotations, the description carries the full burden and does add real behavioral context: it runs live model inference, declares output provenance (source: live), and disclaims clinical use. But it omits cost/latency implications of live inference, whether it is read-only/side-effect free, and any rate or permission constraints.

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 content is relevant but the opening sentence is awkwardly constructed and jargon-dense, requiring re-reading to parse the alt-vs-ref framing. Three short paragraphs are reasonably front-loaded with purpose, but the structure could be tighter and the scorer explanation clearer.

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 explain what the two scorer outputs represent (log fold change vs expression level) and the live-inference provenance, which covers most of what an agent needs. The main remaining gap is the absence of any sibling differentiation for a crowded name-space.

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 the schema already documents chromosome, position, ref, alt, and tissue_type in detail (including format, 1-based hg38, and CURIE examples). The description only implicitly touches tissue filtering via 'per gene and tissue,' adding little beyond the schema, so the baseline 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?

The description states a specific operation: predicting expression for the alternate allele against the reference, naming the concrete scorers (RNA_SEQ for log fold change, RNA_SEQ_ACTIVE for expression level). It is clear on the resource and output semantics, but it never distinguishes itself from sibling tools like predict_expression_impact, compare_alleles, or predict_variant_effect that sound highly overlapping.

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 some context: live inference, applicability to SNVs, indels and MNVs, and that results carry source: live. However, there is no explicit guidance on when to choose this over the many sibling prediction tools (e.g., predict_expression_impact or compare_alleles), leaving the choice to inference.

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