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jean — Molecular Biology & Genomics

load_trace

Read-only

Read a Sanger trace (.ab1 / .scf / .ztr) from this project and hand its BASE CALLS onward as a record, with the per-base quality and the trim bounds beside them. This is what makes a sequencing read a pipeline input: verify it against a reference, align it, gate on its quality. The trace SIGNAL stays here — a record crosses a wire as bases, and a peak cannot be written as one.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
trimNoemit the quality-trimmed read rather than the whole call list. The bounds are the sliding-window mean-phred bounds the chromatogram panel trims by, so panel and pipeline cut at the same base.
_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.
_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.
documentNowhich trace file to read: its name (`read_F.ab1`) or its project file id. A file id is project-specific, so a template ships this unset.
min_qualityNothe mean phred a window must reach to be kept when trimming. Only applies when trim is true.
reverse_complementNoread it on the other strand. A reverse primer's trace is the reverse complement of the strand you are verifying, and a name ending _R is the convention for it.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
traceYeswhat the FILE says about itself: format, instrument comments, call count, trim bounds. Not the signal, which cannot ride a wire
lengthYeshow many bases that is
recordYesthe read as a linear record, ready for any downstream step
sequenceYesits bases, trimmed when trimming is on
ambiguousYeshow many calls are not A, C, G or T: the mixed positions
qualitiesYesper-base phred, parallel to the bases
meanQualityYesthe ARITHMETIC mean of the per-base phred, which is what FastQC plots. Always the higher of the two, because a phred score is a log of an error rate: keep it for comparison with other tools, gate on readQuality
qualityPlotYesper-base phred as a plot along the read, with Q20 (1 error in 100) marked
readQualityYesthe read's own quality: the phred of its MEAN ERROR PROBABILITY, which is what seqkit's --avg-qual reports. Wire THIS into a gate to stop a bad read early
expectedAccuracyYesthe same number as a percentage of bases expected to be correct

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, non-destructive, not open-world), and the description adds genuinely useful behavior: it returns base calls crossed as a record, not the trace signal/peaks, so the agent knows it cannot write raw chromatogram data onward. That is meaningful disclosure beyond the annotations, though it stops short of discussing quality defaults or failure modes.

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?

Four sentences, front-loaded with the read-and-return core, and no wasted preamble. The final 'a record crosses a wire as bases, and a peak cannot be written as one' is slightly ornamental but still conveys the output-type constraint.

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 an output schema present, return-value explanation isn't required, and the description covers what the tool reads, what it emits, and the signal-vs-bases constraint. It's nearly complete for a 6-param nested tool, though it leaves the project/_files/_subject plumbing entirely to the schema.

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 trim, min_quality, reverse_complement, document, _files and _subject in detail. The description adds only general framing about trim bounds and quality, no syntax or format detail beyond the schema, so the baseline of 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 (read) and resource (Sanger trace .ab1/.scf/.ztr) plus the exact output shape: base calls as a record with per-base quality and trim bounds. The clause 'The trace SIGNAL stays here' sharply distinguishes it from the signal-returning siblings like trace_raw_signal.

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

Usage Guidelines3/5

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

The description says what the output enables (verify against a reference, align, gate on quality), which implies downstream usage, but it never states when to pick load_trace over alternatives such as list_traces, trim_trace, or trace_raw_signal. The usage context 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.

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