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Jean — Molecular Biology & Genomics

build_assembly_report

Read-only

Build DnaCauldron's assembly report from an assembly result: the per-construct summary table, the constructs and errors spreadsheets as pandas-compatible CSV, and the Outcome / Number of assemblies stats.

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, for a method that has one — it becomes the report's `enzymes` column, mirroring DnaCauldron's `Type2sRestrictionAssembly.get_extra_construct_data()`. Leave it empty for Gibson, which has no enzyme: an empty column would imply one exists.
errorsNostructured assembly errors — wire the assembly node's `errors` output. These become the errors spreadsheet, which is the most useful thing in a report about a run that did not work.
_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.
productsNothe enumerated constructs — wire an assembly node's `products` output. Each needs `id`, `sequence` and `fragmentNames`, which is what both assembly nodes emit.
warningsNostructured assembly warnings — wire the assembly node's `warnings` output.
assembly_nameNothe name for this assembly: the `assembly_name` column of the summary table and the first field of every errors row.assembly

Output Schema

NameRequiredDescriptionDefault
statsYesthe Outcome / Number of assemblies table, as `compute_stats` produces it
reportYesthe whole report object, including the summary dataframe and the plots decision
errorsCsvYesthe errors spreadsheet — upstream's `errors.csv`, or an empty string when the run had none. Faithful to upstream's own 4-header / 3-field mismatch
partsUsedYesevery part name that appears in at least one construct
summaryCsvYesthe constructs spreadsheet, pandas-compatible CRLF CSV — upstream's `constructs.csv`
summaryTextYesthe report as plain text, for a run record or a note
warningsCsvYesthe warnings spreadsheet, or an empty string when the run had none
constructCountYeshow many constructs the summary table describes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
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's added value is disclosing the output artifacts are CSV spreadsheets and stat fields. It does not say whether files are written to disk or only returned, nor anything about size/rate limits. Helpful context, but not rich behavioral disclosure beyond the annotations.

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 front-loaded sentence with no filler; the colon-separated artifact list is dense but every clause identifies a distinct output. Slightly long for one sentence, but nothing is redundant.

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 7-parameter tool with nested objects, a full input schema and an output schema, the description covers purpose and the produced artifacts, while the schema covers parameter wiring and the output schema covers return shape. The only gap is explicit sequencing guidance relative to the assembly nodes, which the schema partially supplies.

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 each parameter is documented in detail in the schema (including which node output to wire for products/errors/warnings and what the enzyme column means). The description adds only loose mapping between its listed artifacts and those inputs. With the schema doing the heavy lifting, baseline 3 is appropriate.

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 ('Build') and resource ('DnaCauldron's assembly report') and enumerates the concrete artifacts produced: the per-construct summary table, constructs and errors spreadsheets as pandas-compatible CSV, and Outcome / Number of assemblies stats. That is clearly distinguishable from siblings like verify_construct or export_construction_record. It stops short of naming an explicit alternative, but the artifact list makes the purpose unambiguous.

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

Usage Guidelines3/5

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

Usage is only implied by the phrase 'from an assembly result' – an agent can infer it runs after an assembly node, and the schema descriptions reinforce this by telling the caller to wire the assembly node's `products`/`errors`/`warnings` outputs. However, the description itself gives no when-to-use-vs-alternatives guidance and no prerequisites or exclusions (e.g., when to use this instead of a raw export or verify_construct).

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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