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Jean — Molecular Biology & Genomics

by io.github.genmnz
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record_composition

Read-only

What the subject record is MADE OF: molecular weight under its own topology and strand count, GC and AT over the resolved bases, and the per-symbol census with the ambiguity codes broken out.

Input Schema

NameRequiredDescriptionDefault
_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.
doubleStrandedNoweigh BOTH strands (a plasmid or any dsDNA record) rather than the one strand written in the file (an oligo, an RNA, an alignment row). The two answers differ by about a factor of two, which is why it is a parameter and not a guess. Defaults to true, or false when the record is RNA (U and no T), which is also weighed with RNA residue masses.

Output Schema

NameRequiredDescriptionDefault
lengthYessymbols in the record, non-standard ones included
strandsYeshow many strands the mass was taken over: 2, 1, or 0 for a protein where the question does not arise
atPercentYespercent A+T over the same denominator. Null for a protein
gcPercentYespercent G+C over the RESOLVED A/C/G/T bases (`standardCount`), which is Biopython's gc_fraction default (ambiguous="remove") — not over the full length, so it complements `atPercent` exactly. Null for a protein
extinctionYesprotein subjects only: e280 under both cystine conventions; null otherwise
compositionYesone row per standard symbol: code, label, count, and its percent of `standardCount`
nonStandardYesthe symbols the alphabet does not define — Ns, IUPAC ambiguity codes, gaps — with counts and NO share, because they are excluded from the denominator
standardCountYeshow many of `length` are standard — the denominator every share here is over
molecularWeightYesmolecular weight — g/mol for a nucleic acid under `doubleStranded` and the record's own topology, Da for a protein
isoelectricPointYesprotein subjects only (ProtParam, Bjellqvist); null otherwise

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedOutput schema / properties / atPercent / x-unit
      Added value: +"%"
    • addedOutput schema / properties / gcPercent / x-unit
      Added value: +"%"
  2. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds useful behavioral detail: weights are computed under the record's own topology and strand count, statistics are taken over resolved bases, and ambiguity codes are broken out separately rather than silently dropped. It does not discuss defaults, RNA handling, or failure modes, but those live in the schema, so a 3 is appropriate.

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?

A single dense sentence with the scope front-loaded ('What the subject record is MADE OF') followed by the three computed outputs. No filler, though the all-caps emphasis and the fragment structure make it slightly harder to parse than plain prose would.

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?

The tool is a moderate-complexity read-only calculator with an output schema, so return values need not be described. The description plus a fully documented 3-parameter schema covers what an agent needs to call it correctly; only the choice against sibling measurement tools is unaddressed.

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 the doubleStranded parameter is documented in the schema with its default behavior spelled out, so the schema does the heavy lifting. The description only gestures at strand handling via 'strand count'; baseline 3 applies when structured fields already carry parameter meaning.

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 names a concrete computation over a specific object: molecular weight, GC/AT content over resolved bases, and a per-symbol base census for the subject record. That is well beyond restating the name 'record_composition' and lets an agent tell it apart from narrower siblings like gc_content or peptide_mass. It stops short of 5 because it never names an alternative tool or an explicit verb.

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

Usage Guidelines2/5

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

There is no when-to-use or when-not-to-use guidance, and no mention of the many nearby tools (gc_content, protein_properties, melting_temperature) that could plausibly be chosen instead. The only implied scope is 'the subject record', which the schema already establishes.

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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