jean — Molecular Biology & Genomics

enzyme_collection

Read-only

Resolve one of your saved enzyme collections to the enzyme names in it, so a later step can scan, digest or design with 'my Golden Gate set' by name instead of whatever happens to be selected. Names the collection, says which of its enzymes the cut catalog can resolve and which it cannot, and — when a record is open — how many times each one cuts it. Left unnamed it answers for the collection that is currently active, and says that is what it did.

Input Schema

TableJSON Schema

Name	Required	Description
`name`	No	the collection to resolve, by the name it has in the Enzyme Collections panel. Left unset, the active collection is used; with none active, the whole catalog is in scope and this says so rather than returning an empty set.
`_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.

Output Schema

TableJSON Schema

Name	Required	Description
`count`	Yes	how many enzymes resolved — branch on this rather than counting the array
`cutting`	Yes	per enzyme, how many times it cuts the OPEN record — absent when nothing is open, because a cut count with no molecule behind it is a number nobody asked for
`enzymes`	Yes	the enzyme names in the collection, ready to wire into any tool's `enzymes` parameter — the resolvable ones only, so a downstream digest never refuses on a name this step already knew was unusable
`available`	Yes	every collection you have, by name, with its size and whether it is the active one — so a run that named the wrong collection can say what the right names were
`collection`	Yes	the collection this answered for, or 'the whole catalog' when nothing is scoped
`unresolved`	Yes	names in the collection that the bundled cut catalog does not carry, usually a custom enzyme defined in the panel or a supplier spelling. Reported rather than dropped: a set that silently shrinks is the reason a digest comes back short
`singleCutters`	Yes	the enzymes cutting the open record exactly once — the ones a linearization or a directional clone can use. Empty when nothing is open

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 20, 2026

TDQS

A4.1/5.0

Behavior4/5

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

The annotations already establish a read-only, non-destructive, non-open-world operation, so the safety profile is covered. The description adds useful behavioral detail: it resolves the collection by name, reports which enzymes the cut catalog can and cannot resolve, and when a record is open reports cut counts. It also discloses default behavior when no name is given.

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 front-loaded with the core purpose and then covers outputs and default behavior. It is somewhat long but each sentence carries distinct information about resolution, reporting, or default scope. It could be slightly tighter, but it is not padded.

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 three parameters, full schema coverage, annotations, and an output schema, the description is largely complete. It explains what is resolved, what is reported, and what happens when no collection is named. Remaining gaps around sibling alternatives are minor because the annotations and schema cover much of the rest.

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 descriptions already document name, _files, and _subject in detail. The description reiterates the unnamed-collection default but adds no syntax or format information beyond what the schema already provides. This is the baseline when the schema carries parameter semantics.

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?

The description states a specific verb and resource: resolve a saved enzyme collection to the enzyme names in it. It also distinguishes the outcome from siblings by explaining that it reports resolvable versus unresolvable enzymes and, when a record is open, per-enzyme cut counts. An agent can identify this as a collection-lookup tool rather than a design or digestion tool.

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?

It gives a clear use context: later steps can scan, digest, or design with a named collection instead of relying on current selection. It also explains the default behavior when the collection is unnamed. However, it does not explicitly name alternatives such as save_enzyme_collection or enzyme_cut_counts, nor does it state when not to use this 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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