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jean — Molecular Biology & Genomics

call_bases_from_trace

Read-only

Call the bases of a Sanger trace from the signal, discarding the instrument's calls and deriving the bases, their positions and their quality from the peaks. The read can come back a DIFFERENT LENGTH than the file's. This ANSWERS the question; adopt_trace_calls is what puts the answer onto the read.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableNothe instrument/polymer calibration table to score against. The same signal scores differently under each, so a quality value is only interpretable with the table named. Defaults to ABI 3730 POP-7.3730pop7
_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.
documentNowhich trace to run on: a file name (`read_F.ab1`) or its project file id. Leave unset to use the trace tab on screen. A file id is project-specific, so a template ships this unset.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
basesYeshow many bases the reading called
meanQualityYesthe mean Phred of the reading, on the calibration table it names
instrumentBasesYeshow many the FILE carries, so a gate can see a de-novo reading change the read's length

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already cover the safety profile (readOnlyHint=true, destructiveHint=false), and the description adds genuinely non-obvious behavior: that instrument calls are discarded, bases/positions/quality are re-derived from peaks, the returned read may be a DIFFERENT LENGTH than the file, and that this operation does not itself modify the read. This is meaningful behavioral disclosure beyond structured data.

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?

Three tight sentences, front-loaded with the action, then the surprising behavioral note (different length), then the sibling relationship. Every sentence carries distinct information and none is redundant.

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

Completeness5/5

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

For a non-trivial tool with an output schema (so return values needn't be explained), full annotation coverage, and 100% param documentation, the description supplies exactly the missing pieces: what it derives, the length caveat, and its relationship to the adopting sibling.

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 schema already documents `table`, `_files`, `_subject`, and `document`. The description adds no parameter-level detail (e.g., how `table` affects scoring), so the baseline 3 applies.

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?

States a specific verb+resource ('call the bases of a Sanger trace from the signal') and clarifies the mechanism (discarding instrument calls, deriving from peaks). It explicitly distinguishes itself from the sibling `adopt_trace_calls`, so an agent can tell the two apart without opening a schema.

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?

Names the alternative (`adopt_trace_calls`) and states the division of labor: this tool ANSWERS the question while the sibling applies the answer onto the read. Clear routing context, though it gives no explicit exclusions or when-not guidance (e.g., versus `call_mixed_bases_from_trace`).

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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