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

Annotations indicate readOnlyHint=true and idempotentHint=true, and the description adds details about the trimming algorithms (ungapped sliding-suffix adapter match, BWA-style quality trim) and the outcome (drops short reads, returns stats). This adds value beyond annotations.

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 a single dense paragraph that efficiently states the purpose, algorithm, and output. It is appropriately sized and front-loaded, though could be slightly more concise.

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 tool's moderate complexity and absence of output schema, the description adequately covers purpose, algorithm, and return values (trimmed FASTQ plus stats). It lacks error conditions or input format verification, but schema covers input format.

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 mentions the minLength parameter implicitly by saying 'drops reads below a minimum length', but does not add significant meaning beyond what the schema already provides for each parameter.

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 it trims FASTQ reads with adapter and quality trimming, specifying the exact algorithm and returning trimmed FASTQ plus statistics. The verb 'trim' and resource 'FASTQ reads' are specific, and it distinguishes from sibling tools like fastq_qc_report which focuses on QC reporting.

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 implicitly defines usage for trimming FASTQ with adapter and quality trimming, but does not explicitly exclude other use cases or name alternative tools. It provides clear context but lacks exclusions.

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