Jean — Molecular Biology & Genomics

copy_number_findings

Read-only

Scan every indexed chromosome of an Affymetrix copy-number container and report what the file itself called: gains, losses and stretches of homozygosity, with their positions, marker counts and spans, plus a per-chromosome summary.

Input Schema

Name	Required	Description
`file`	No	which copy-number file in this project, by name. Unset, it is the project's only one — and it refuses rather than guessing when there is more than one.
`_files`	No	The 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.
`_subject`	No	The 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.
`data_set`	No	which data set to scan, by name. Unset is the file's FIRST, which is what the panel opens on.
`min_bases`	No	ignore any run spanning fewer bases than this. Default 0, for the same reason as min_markers. Note a single-marker run spans 0 bases.
`min_markers`	No	ignore any run shorter than this many markers. The default counts everything the file called, including single markers, because a reporting floor belongs to the laboratory and not to this tool.

Output Schema

Name	Required	Description
`bed`	Yes	the same calls as a UCSC BED track, ready for IGV, the UCSC browser or bedtools: 0-based half-open, one row per finding, colored by kind through itemRgb, with the producer's confidence in the score column (0 where the file states none) and the genome build on the `track db=` line when the container names one. The JSON `findings` above carry the file's own inclusive marker positions; this output is the same calls converted once, by the same writer the Export panel uses
`source`	Yes	which route answered: `segments` means the producer's own segment calls, which is what a CYCHP written by ChAS carries; `markers` means the per-marker state columns, which is what a CNCHP carries. Different provenance for the same question, so a pipeline comparing two files can tell which it got
`summary`	Yes	what was found, across how many chromosomes and markers
`findings`	Yes	every gain, loss and stretch of homozygosity, as the file called them: kind, chromosome, startPosition, endPosition, markerCount, bases, and — where the file states them — state and stateLabel (the copy-number state; absent on an LOH finding, which is not a copy-number call), confidence (the producer's own, 0..1) and mixture (mosaic fraction, signed as the file signs it, so a mosaic loss and a mosaic gain stay distinguishable). No cytoband: naming a band needs a genome build, and this node is given none
`chromosomes`	Yes	per chromosome: markers read, and the counts and spans of gains, losses and LOH runs

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 20, 2026

TDQS

A3.7/5.0

Behavior4/5

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

The annotations already establish that this is a read-only, non-destructive, non-open-world operation, so the safety profile is covered. The description adds meaningful behavior beyond that: it scans every indexed chromosome and reports the file's own calls rather than performing new calling, along with positions, marker counts, spans, and a per-chromosome summary.

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?

The description is a single front-loaded sentence with no filler, and the core action and outputs are stated immediately. The enumerated output details are useful but make the sentence somewhat dense.

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?

For a read-only reporting tool with an output schema and fully described parameters, the description is largely complete: it explains what is scanned and what is returned. The main remaining gap is explicit routing among sibling copy-number tools, but annotations and schema fill in the operational details.

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 parameter schema carries the burden of explaining file, data_set, min_bases, min_markers, _files, and _subject. The description adds no parameter-specific meaning beyond the general scope of scanning all indexed chromosomes. This meets the baseline for high schema coverage but does not exceed it.

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

Purpose4/5

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

The description uses a specific verb, "Scan," and a precise resource, "every indexed chromosome of an Affymetrix copy-number container," and states the reported outputs. It is clear what the tool does, though it does not explicitly distinguish itself from the many sibling copy_number_* tools.

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?

Usage is implied: it is for reporting what the file itself called across all indexed chromosomes, including gains, losses, homozygosity stretches, and a per-chromosome summary. However, it gives no explicit when-to-use versus alternatives guidance despite the dense set of copy-number siblings such as copy_number_regions, copy_number_loh, and copy_number_segment.

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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