Read a raw DNA file on this computer

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

Annotations only cover the safety profile (readOnly, idempotent, non-destructive, openWorld); the description goes well beyond by disclosing the four possible per-variant states, the conditional gating of disease-risk genes, the chromosome-X/sex dependency for G6PD, and a required downstream behavior (defer health decisions to a clinician and validated test). These are operational rules an agent cannot infer 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?

Efficient and front-loaded: purpose, formats, return states, then parameter guidance, then safety constraints. It is on the dense/long side and the state enumeration partially overlaps the output schema, but every sentence carries operational weight — none is filler.

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?

Given an output schema exists, the description needn't enumerate return values yet does so usefully, and it covers the domain-specific risks of consumer genetics data (gene gating, non-diagnostic framing, clinician referral). Nothing an agent needs to call this correctly — input source, scoping, and interpretation limits — is missing.

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 coverage is 100%, so the baseline is 3; the description still adds meaning beyond the schema by framing `genes` as 'what the user asked about' with a worked example and tying `sex` to a specific consequence (G6PD chromosome X positions). It does not restate parameter types or defaults, which is correct given the schema already handles that.

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 precise verb+resource pair ('Read the user's raw DNA file') and immediately narrows scope with supported vendors and file formats (.txt, .csv, .zip). The four output states (read, no_call, not_in_file, unexpected_letters) make the tool's contract concrete and clearly distinguish it from the lookup_drug_gene sibling, which operates on interpreted data rather than raw files.

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 tells the agent when to pass `genes` ('what the user asked about, e.g. ["CYP2C19"] before discussing clopidogrel') and imposes a hard exclusion rule: APOE, BRCA1 and HFE 'are read only when named in `genes`, so do not offer or report them unless the user asks for them by name.' It also states the boundary of interpretation ('a count at one position is not a metabolizer status, diplotype, diagnosis or dose') and where to route health-relevant findings.

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