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jean — Molecular Biology & Genomics

mask_sequence

Read-only

Mask the parts of a sequence a similarity search should not seed on, using BLAST's own three maskers: DUST for compositionally biased DNA (poly-A, simple repeats), SEG for the protein equivalent, and WindowMasker for repeats that are ordinary in composition but occur far more often than chance allows in the sequences given. Emits the soft- and hard-masked sequences and the masked intervals, so a pipeline can mask before it searches rather than explaining an empty hit table afterwards.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hicutNoSEG's K2, the extension complexity in bits. Only applies when masker is seg.
levelNoDUST's T. Higher masks less. Only applies when masker is dust.
locutNoSEG's K1, the trigger complexity in bits. Only applies when masker is seg.
_filesNoThe project: record references shaped like _subject. Their records become library documents a tool names in sequences/parts/document; a trace or alignment is found by file name.
maskerNowhich masker. dust and windowmasker take DNA; seg takes protein. Values: dust (DUST · biased DNA composition), seg (SEG · biased protein composition), windowmasker (WindowMasker · over-represented DNA).dust
windowNothe scored window's width. 0 takes each masker's own default.
contextNoWindowMasker only: the other sequences whose statistics define 'over-represented'. Its thresholds come from this SET, so wiring one plasmid asks whether a stretch is unusual for that plasmid, not for the organism. Only applies when masker is windowmasker.
_subjectNoThe record to act on: exactly one of sequence, accession (+source), sample (an id from list_samples) or file ({name, text} or {name, base64}); record_index picks one record of several.
sequenceNothe sequence to mask. Wire a record or a sequence output, or paste it. Left empty, the open record is used.
unit_sizeNoWindowMasker's n-mer length. 0 derives it from the length of everything given, the way the tool does. Only applies when masker is windowmasker.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
maskedYesthe sequence soft-masked (lower case), which is what BLAST reads as masked
intervalsYesthe masked stretches, 0-based inclusive
hardMaskedYesthe sequence with the masked stretches replaced by N (or X for a protein)
provenanceYesthe masker, the parameters it really used, and for WindowMasker the derived thresholds and the set they came from
maskedFractionYeswhat share of the sequence was masked, 0 to 1. Wire into a $when to refuse a query that is mostly gone

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare a safe, read-only, closed-world computation, so the bar is lower. The description adds real behavioral context beyond that: it emits both soft- and hard-masked sequences plus masked intervals, and notes that WindowMasker thresholds are derived from the context SET rather than organism-wide.

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

Conciseness4/5

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

Two sentences, front-loaded with the core action and immediately followed by the masker taxonomy and the output rationale. Dense and mostly waste-free, though the long enumerations make it heavier than strictly necessary.

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 a full output schema covering return values and annotations covering the safety profile, the description supplies the missing motivation and masker-selection logic. It could go further by tying itself explicitly to the search/alignment siblings it is meant to precede, but nothing an agent needs to invoke it correctly is missing.

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%, so the schema already documents every parameter, including the masker-specific applicability of hicut, locut, level, window, unit_size and context. The description reinforces the DNA/protein split but adds no new syntax or defaults, so the baseline 3 applies.

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?

States a specific verb (mask) plus the exact resource and scope: the regions a similarity search should not seed on. It names and differentiates all three maskers (DUST, SEG, WindowMasker) with what each targets, so an agent can act without opening the schema.

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?

Clearly frames when this belongs in a pipeline (mask before searching rather than explaining an empty hit table afterwards) and which masker suits which substrate (DNA vs protein). It stops short of naming the search sibling it should precede or stating exclusions, so it is clear context without explicit alternatives.

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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