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Jean — Molecular Biology & Genomics

design_split_sites

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Decide where to CUT one sequence into Golden Gate fragments, optimising the split positions and the overhangs they create together.

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.
tracesNohow many ranked alternatives to return. The best arrangement is rarely the only acceptable one, and the runner-up often avoids a site you care about.
datasetNothe measured ligation matrix to score against. OOGGA's own published choice is the T4 18 h 37 C set. Values: BsaI-HFv2 (BsaI-HFv2, Golden Gate cycling (4 nt)), BsmBI-v2 (BsmBI-v2, Golden Gate cycling (4 nt)), Esp3I (Esp3I, Golden Gate cycling (4 nt)), BbsI-HF (BbsI-HF, Golden Gate cycling (4 nt)), SapI (SapI, Golden Gate cycling (3 nt)), T4-01h-25C (T4 DNA ligase, 1 h at 25 C (4 nt)), T4-01h-37C (T4 DNA ligase, 1 h at 37 C (4 nt)), T4-18h-25C (T4 DNA ligase, 18 h at 25 C (4 nt)), T4-18h-37C (T4 DNA ligase, 18 h at 37 C (4 nt)). Advanced.T4-18h-37C
_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.
sequenceNothe sequence to fragment, in one piece. Leave it empty to fragment the open record.
fragmentsNopin the number of fragments instead of letting the search choose. Leave empty to take whatever the length window allows.
exclude_toNoend of that span, exclusive. Only applies when exclude_from is set. Advanced.
max_lengthNolongest allowed fragment, in bases — the vendor's upper limit, or the length you can sequence in one read.
min_lengthNoshortest allowed fragment, in bases — usually what your synthesis vendor will accept.
exclude_fromNostart of a span no cut may fall in — a feature you need kept intact. Use with exclude_to. Advanced.
alien_overhangsNojunctions already committed elsewhere in the assembly (a fixed vector's own ends), which this set must not collide with. Advanced.
fidelity_weightNoexponent on the running FIDELITY — raise it to favour junctions that ligate to the right partner rather than a mismatched one. Advanced.
efficiency_weightNoexponent on the running ligation EFFICIENCY — raise it to favour junctions that ligate readily. Efficiency and fidelity are different failure modes: a junction can ligate eagerly and promiscuously. Advanced.
max_overhang_identityNomost positions two overhangs in the set may share before they are treated as confusable. Lower is stricter and rules out more arrangements. Advanced.

Output Schema

NameRequiredDescriptionDefault
scoreYesthe objective for the winning arrangement: net efficiency^w x net fidelity^w
breaksYesthe winning arrangement's cut positions, in reading order
reportYesthe whole result, every arrangement in full
datasetYesthe measured matrix actually scored against
fragmentsYesthe fragments to order: sequence, span, length and the overhang at each end. Consecutive fragments overlap by exactly the four-base junction
overhangsYesthe junctions the winning arrangement creates — wire this straight into score_overhang_fidelity to grade the set it chose
candidatesYeshow many arrangements were feasible at all under these constraints
alternativesYesthe other ranked arrangements, each with its own breaks, score and junctions — the best is rarely the only acceptable one
net_fidelityYesnet fidelity across every junction, 0-1
fragment_countYeshow many fragments the winning arrangement needs
net_efficiencyYesnet ligation efficiency across every junction, 0-1

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
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 that the tool jointly optimizes cut positions and the resulting overhangs, which is useful behavioral context, but it does not disclose determinism, scoring behavior, or output characteristics beyond what the schema and output schema carry.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single front-loaded sentence with no filler. It is compact and readable, though its brevity is also the source of the missing usage guidance noted elsewhere.

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 has 14 parameters, nested objects, and an output schema, but the rich schema documents every parameter and the output schema covers return values. The description supplies the core purpose and optimization target; the main contextual gap is when to select this tool over adjacent design and assembly tools.

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 every parameter, including the advanced scoring and exclusion controls, is already documented in the schema. The description adds no parameter-specific meaning beyond the general purpose and therefore sits at the baseline.

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 has a specific verb ('Decide where to CUT') and resource ('one sequence into Golden Gate fragments'), and it states the joint optimization of split positions and overhangs. It does not explicitly name a sibling such as design_overhang_set or golden_gate_assemble, so the differentiation is implicit rather than verbalized.

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 explicit when-to-use statement, no prerequisites, and no named alternatives. The only guidance is the implied context of cutting one sequence for Golden Gate, which a knowledgeable agent could infer but which does not meet the rubric's requirement for routing guidance.

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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