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Construct QC linter

construct_qc
Read-onlyIdempotent

Lint a coding DNA sequence for premature stops, internal RBS/polyA motifs, unwanted restriction sites, GC extremes and repeats.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
gcLowNoGC% below this flags an AT-rich window.
gcHighNoGC% above this flags a GC-rich window.
gcWindowNoSliding-window size (nt) for GC-extreme scanning.
sequenceYesNucleotide sequence (raw or FASTA; IUPAC accepted).
frameStartNo1-based nucleotide where the reading frame begins.
avoidEnzymesNoEnzyme names whose internal sites should be flagged as errors. Matched against the curated common-enzyme set plus the Golden Gate Type IIS enzymes (BsaI, BbsI, Esp3I/BsmBI); an unrecognised name is rejected, never skipped.
homopolymerMinNoMinimum run length to flag a homopolymer.
crypticOrfMinAaNoMinimum peptide length (aa) for a hidden alternate-frame ORF to be flagged.

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds behavior by enumerating the features it flags, which suggests the output will be a report of those issues. It does not contradict the annotations and adds useful context beyond what annotations declare, though it does not specify output format or error handling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that front-loads the verb 'Lint' and immediately enumerates the checks in a compact list. Every word contributes meaning, and there is zero fluff or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 8 parameters and no output schema, the description plus the rich schema annotations cover the behavior well. The absence of an explicit return-format description is a minor gap, but the term 'lint' implies a report, and the enumerated checks give a clear picture of what will be flagged. The tool's scope is adequately complete for selection and invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and every parameter (sequence, gcLow, gcHigh, gcWindow, frameStart, avoidEnzymes, homopolymerMin, crypticOrfMinAa) has a rich description and defaults. The tool description itself does not discuss parameters, but the schema fully carries that burden, so the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Lint') and a specific resource ('coding DNA sequence'), and enumerates the exact checks it performs: premature stops, internal RBS/polyA motifs, unwanted restriction sites, GC extremes, and repeats. This clearly distinguishes it from siblings like gc_content or restriction_sites, which target only a single check.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description conveys a clear use case: comprehensive QC of a coding DNA construct. It implies that this tool should be used when multiple sequence features need to be validated at once, but it does not explicitly name alternatives or state when not to use it. Hence it provides clear context without exclusions.

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

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TDQS

A3.6/5.0
Disambiguation4/5

Most tools have highly specific purposes (e.g., crispr_grna_design vs base_editing_design vs prime_editing_design). However, there is some overlap in sequence analysis tools (characterize_sequence, sequence_report) and plasmid annotation tools (plasmid_annotate vs plasmid_deep_annotate) which could cause confusion.

Naming Consistency3/5

The naming pattern is largely consistent with snake_case verb_noun or noun_descriptor (e.g., primer_design, plasmid_annotate, fastq_trim). However, there are exceptions like 'batch', 'workflow', 'gc_content', and 'cloning_diagnose' which don't follow the verb_noun pattern consistently. Also, some names are phrases like 'golden_gate_from_parts'.

Tool Count2/5

With 101 tools, this server is extremely large and likely overwhelming for agents. Even for a comprehensive bioinformatics toolkit, this exceeds a manageable scope, risking agent confusion and inefficient tool selection. A more modular approach would be advisable.

Completeness4/5

The tool surface covers a wide range of bioinformatics workflows including sequence analysis, primer design, cloning, CRISPR, NGS, expression analysis, and data export. There are minor gaps such as lack of a dedicated protein structure prediction tool and limited off-target genome coverage, but overall the set is impressively complete for its domain.

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