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score_overhang_fidelity

Read-only

Score a Golden Gate junction (fusion-site) set against MEASURED T4 DNA ligase end-joining data.

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.
enzymeNothe Type-IIS enzyme the reaction uses, which picks that enzyme's own measured matrix when one exists. Only applies when dataset is not given.
datasetNoscore against this measured matrix instead of the one the enzyme implies. 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)).
_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.
remediesNoalso compute what to CHANGE: the drop-the-worst repair, and replacement candidates for each flagged junction. Off makes the run cheaper on a large set.
overhangsYesthe junction overhangs, one per junction, top strand (e.g. AATG, GCTT). Wire `golden_gate_assemble.overhangs` here, or list them.
replacements_per_junctionNohow many replacement candidates to rank per flagged junction. Advanced.

Output Schema

NameRequiredDescriptionDefault
flagsYesweak, self-misannealing and cross-misannealing junction indices, plus the structural verdict
worstYesthe weakest junctions, worst first: what to change to raise the score
repairYesthe drop-the-worst repair: which junctions to remove, what is left, and the fidelity that leaves. Null when `remedies` is off
datasetYesthe measured matrix actually scored against
percentYesthe same number as a percentage, which is how every incumbent reports it
fidelityYesexpected fraction of fully-correct assemblies, 0-1
junctionsYesper junction: overhang, correct/total measured events, its own fidelity, Watson-Crick strength, and its strongest mismatch partners
meaningfulYesfalse when a STRUCTURAL error makes the fidelity number misleading rather than merely bad: do not present `fidelity` on its own when this is false
replacementsYesper FLAGGED junction, the best overhangs to swap in, each with the whole set’s fidelity after the swap. Empty when `remedies` is off
atMeasurementCeilingYestrue when NO mismatch ligation was measured between any two junctions, so the score is exactly 100%: the floor the source experiment can resolve, not a guarantee

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedOutput schema / properties / percent / x-unit
      Added value: +"%"
  2. First observed

TDQS

B3.3/5.0
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 one genuinely useful behavioral fact — that scoring uses measured empirical ligation data rather than a heuristic — but says nothing about what happens with unmatched or duplicate overhangs, or how 'remedies' alters the run.

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?

One front-loaded sentence with no filler, hedging, or redundant restatement of the title or schema. Every word carries information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, return values need not be explained, and annotations carry the safety profile. However, for a 7-parameter tool with nested record objects and a remedies side-computation, the description never signals the design→score workflow or the cheap-run tradeoff, leaving meaningful context gaps for such complexity.

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% (including a fully enumerated dataset list and the note that enzyme only applies when dataset is not given), so the baseline of 3 is appropriate. The description adds no parameter meaning of its own, and its emphasis on 'T4 DNA ligase' sits awkwardly beside a dataset enum dominated by Type-IIS enzyme matrices.

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?

States a specific verb+resource pair: 'Score a Golden Gate junction (fusion-site) set', with the alias 'fusion-site' clarifying terminology. The scoring basis ('against MEASURED T4 DNA ligase end-joining data') separates it from design_overhang_set, check_golden_gate_parts and golden_gate_assemble, but no sibling is named explicitly and the T4-only framing understates that the tool also scores Type-IIS enzyme matrices.

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 guidance, no statement of prerequisites (e.g. that you should already have an overhang set from design_overhang_set or golden_gate_assemble), and no named alternative for related questions such as part-level checks. Usage is only inferable from the single purpose sentence.

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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