qc_maf_filter

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

With no annotations provided, the description effectively discloses that the tool is non-destructive ('does not modify Gigwa'), writes a CSV file, and computes statistics. It does not detail side effects like file overwriting, but the main behavioral traits are 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 concise with four sentences, front-loading the core purpose. Every sentence adds value, no redundancy, and the structure is logical.

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 the complexity (7 params, output schema exists), the description covers the key aspects: purpose, behavior, output file, and performance advice. It lacks detailed CSV format info but the output schema likely covers that, so it is sufficiently complete.

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 baseline is 3. The description adds context about the two methods (vcf vs allelematrix) and performance tip, but does not significantly enrich individual parameter meanings beyond the schema descriptions.

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 clearly states the tool reports markers that would be filtered by MAF/missingness without applying changes, with specific verb and resource. It distinguishes itself from siblings like qc_call_rate by focusing on MAF and missingness filtering, matching the tool name exactly.

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 provides clear when-to-use context: it is a report-only tool for previewing filter outcomes before modification. It also gives guidance for large datasets (pass method='allelematrix' + max_markers). However, it does not explicitly state when not to use it or list alternative tools.

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