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jean — Molecular Biology & Genomics

read_rdml_run

Read-only

Read an instrument's RDML export - the open qPCR exchange standard, v1.0 to v1.4 - and hand back one run's contents as the same tables every other qPCR tool here takes. This is the step every qPCR analysis starts from. Lists what each run actually holds (amplification curves, melting curves, instrument Cq values, digital-PCR partition counts with the partition volume the file declares) before anything is imported, so a run is chosen on what is in it rather than on its name. Takes the UNCOMPRESSED XML: a .rdml archive is a zip, and the tool vocabulary here has no file input.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
runNowhich run to read, 0-based across every experiment in the file in document order. A file routinely holds several; `summary` lists them all whatever this is set to.
tableNowhich table to return for the chosen run. `summary` reads the file without importing anything. The other four are exactly what the panel's four `Send to ...` buttons produce, so a value imported here and one imported there cannot differ. Values: summary (Summary - what every run in the file holds), curves (Amplification curves - Cycle,<reaction>,...), cq (Instrument Cq values - the wide Ct table plus its group column), genorm (Instrument Cq values - long Target,Sample,Cq), melt (Melting curves - Temperature,<reaction>,...), partitions (Digital PCR partition counts - Well,Sample,Target,Positives,Partitions).summary
_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.
rdml_xmlYesthe RDML document as XML text - the `rdml_data.xml` member of a `.rdml` archive, or a bare `.xml` export. Not base64 and not a file path.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsYesdata rows in `table`, excluding its header
runsYesevery run in the file and what it holds - reactions, curves, melt curves, instrument Cq values, partition counts, the declared partition volumes, targets and samples
tableYesthe chosen run's table, as the text the matching tool's own parser takes. Empty when the run has nothing of that kind - which is a fact about the run, not a failure
groupsYesfor `cq`: one sample name per row of the Ct table, already aligned to it. The group column relative quantification needs
omittedYeswhat the import deliberately left out and why - wells whose Cq is RDML's -1 `not available`, and samples whose replicates do not square up across targets. Never padded and never zero-filled (a Ct of 0 is a fabricated measurement)
versionYesthe RDML version the file declares (1.0-1.4). The reader's behaviour differs by version and a table without it is not reproducible

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 readOnly/destructive/openWorld, so the bar is lower, and the description still adds real behavioral context: it accepts only uncompressed XML (a .rdml archive is a zip), there is no file input in the vocabulary, summary reads without importing, and it lists what a run holds before import. It does not describe output tables in detail, but an output schema exists.

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 core verb and resource, then the usage rationale, then the input-format constraint. Dense but each sentence carries distinct information; slightly verbose in the middle sentence enumerating run contents.

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 tool with a full schema and an output schema, the description covers what an agent needs: what it does, when to reach for it, and the input constraint. The unexplained _subject/_files params are a minor gap but their schema descriptions carry the load.

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 run, table, rdml_xml and the enum. The description echoes the run/table semantics (0-based runs, summary lists all) but adds no syntax or format detail beyond the schema. Baseline 3 is correct; note it never mentions the _subject/_files parameters at all.

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 and resource: 'Read an instrument's RDML export' and 'hand back one run's contents as the same tables every other qPCR tool here takes.' It pins down scope (one run), standard (open qPCR exchange standard v1.0-v1.4), and output shape, distinguishing it from the other qPCR tools in the vocabulary.

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?

'This is the step every qPCR analysis starts from' plus the framing that runs are chosen on content rather than name gives a clear entry-point context. It implies downstream consumers ('the same tables every other qPCR tool here takes') and warns about the compressed-input constraint, but names no concrete alternative sibling tool.

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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