qc_heterozygosity

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

With no annotations provided, the description carries the burden of behavioral disclosure. It clearly states that the tool writes heterozygosity_samples.csv, flags samples beyond a standard-deviation threshold, and describes a method-dependent performance tradeoff. It does not discuss permissions or non-destructiveness, but the QC context and output-file disclosure make the behavior reasonably transparent.

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 description is four sentences with no filler. The first sentence delivers the core purpose, and subsequent sentences add interpretation, threshold behavior, output artifact, and large-set guidance. Every sentence earns its place.

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 that an output schema exists and the input schema covers all parameters, the description supplies the remaining needed context: what the tool detects, how it flags outliers, what it writes, and how to scale to large datasets. An agent can confidently select and invoke this tool without needing further explanation.

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?

The input schema already documents all six parameters, so the baseline is 3. The description adds value by linking outlier_sd to the flagging rule and by explaining that method='allelematrix' plus max_markers avoids a full VCF export. This goes beyond the schema's parameter descriptions and gives actionable performance guidance.

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 action: 'Per-sample observed heterozygosity QC, flagging outliers.' It also gives biological interpretation of high/low Ho, which distinguishes this QC metric from siblings like qc_call_rate or qc_maf_filter. The verb and resource are clear and unambiguous.

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?

The description gives clear guidance on interpreting high vs. low Ho and explicitly recommends method='allelematrix' plus max_markers for large datasets to avoid a full VCF export. It does not name sibling QC tools or list when not to use it, so it stops short of a full exclusionary routing guide.

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