qc_duplicate_accessions

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

Annotations are absent, so the description carries the full behavioral burden, and it delivers: it discloses the algorithm (pairwise IBS allele-sharing), the default subsampling to max_markers 'for speed', the explicit output side effects ('Writes duplicate_pairs.csv and duplicate_groups.csv'), and a performance-optimized code path. It could additionally state whether the underlying data is mutated, but the CSV writing is explicitly disclosed.

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?

Four tightly written sentences, front-loaded with the core purpose then algorithm, defaults, outputs, and tuning tip in order of importance. Every sentence earns its place; there is no fluff, repetition, or marketing language.

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 an output schema present, return values need no explanation. The description covers the algorithm, the grouping threshold semantics, default behavior with its override, the written artifacts, and performance scaling guidance. Only minor gaps remain, such as expected runtime for large variant sets, but nothing required to invoke or interpret the tool correctly 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 description coverage is 100%, so per the baseline the schema already documents all six parameters. The description adds a little extra meaning — the speed motivation for max_markers and the large-set recommendation for method='allelematrix' — but these are light nuances rather than substantial semantic additions beyond the schema.

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?

Opens with a specific verb+resource pair: 'Detect duplicate / clonal accessions via pairwise identity-by-state (IBS)', then explains the grouping mechanism (pairs at/above similarity_threshold become duplicate sets). The pairwise IBS mechanism and duplicate-grouping terminology clearly set it apart from sibling QC tools like qc_call_rate and qc_heterozygosity.

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?

Gives clear context — 'the core genebank cleaning check for mislabelled duplicates and clones' — and practical usage guidance such as setting max_markers to 0/None to use all markers and passing method='allelematrix' for large sets. However, it never names the sibling QC tools as alternatives or says when NOT to use this tool, so the exclusion logic is left to inference.

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