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Jean — Molecular Biology & Genomics

discover_annotation_contradictions

Read-only

Find the signal peptides or transmembrane segments in reviewed human UniProt that a sequence predictor contradicts.

Input Schema

NameRequiredDescriptionDefault
alphaNofalse discovery rate at which an annotation is called contradicted.
_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.
featureNowhich annotation to test: signal peptides or transmembrane segments. Values: signal (Signal peptides), transmembrane (Transmembrane segments).signal
_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.
decodingNotransmembrane only: which HMM-TM decoder labels the residues. N-best is left out: it takes minutes per long protein, and the corpus has 5,231. Values: viterbi (Viterbi), posterior-viterbi (Posterior-Viterbi), optimal-accuracy (Optimal accuracy). Only applies when feature is transmembrane. Advanced.viterbi
predictorNosignal only: von Heijne's matrix asks whether signal peptidase would cut where UniProt says; DeepSig asks whether the protein has a signal peptide at all (it loads 9.8 MB of network weights and runs twenty networks per protein, so it is far slower than the matrix). Values: von-heijne (von Heijne matrix), deepsig (DeepSig). Only applies when feature is signal.von-heijne
correctionNoBenjamini–Hochberg (independent or positively dependent tests; conformal p-values against one calibration set are positively dependent) or Benjamini–Yekutieli (any dependence; less power). Values: BH (Benjamini–Hochberg), BY (Benjamini–Yekutieli).BH

Output Schema

NameRequiredDescriptionDefault
countYeshow many annotations are contradicted
resultYesthe full result, every tested annotation included
selfCheckYeshalf the experimental features tested against the other half: raw p ≤ α should be near α of them, and FDR calls near none
contradictedYesthe annotations contradicted at the chosen false discovery rate: accession, gene, span, statistic, p and q

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / decoding / description
      Previous value: -"transmembrane only: which HMM-TM decoder labels the residues. N-best is left out: it takes minutes per long protein, and the corpus has 5,231. Values: viterbi (Viterbi), posterior-viterbi (Posterior-Viterbi), optimal-accuracy (Optimal accuracy). Advanced."New value: +"transmembrane only: which HMM-TM decoder labels the residues. N-best is left out: it takes minutes per long protein, and the corpus has 5,231. Values: viterbi (Viterbi), posterior-viterbi (Posterior-Viterbi), optimal-accuracy (Optimal accuracy). Only applies when feature is transmembrane. Advanced."
  2. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare the tool read-only, non-destructive, and closed-world, so the safety profile is covered. The description adds that it scans reviewed human UniProt and looks for predictor contradictions, but it does not disclose that _subject/_files can supply arbitrary records, nor does it explain the statistical correction (alpha, BH/BY) central to the result. The scope statement may even mislead an agent into thinking only the reviewed human UniProt corpus is available.

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 a single front-loaded sentence with no filler. It is appropriately terse, though its density leaves scope details implicit rather than explicit.

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?

Output schema exists, annotations cover safety, and the schema is richly documented, so return values and parameter details need not be repeated. However, for a 7-parameter statistical discovery tool, the one-sentence description is thin: it omits alternatives and does not reconcile its 'reviewed human UniProt' scope with the flexible _subject/_files inputs. An agent has enough to guess the purpose but not enough to confidently select or configure it.

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 the schema already defines feature, alpha, decoding, predictor, correction, and the _subject/_files record shapes in detail. The description only echoes the feature concepts ('signal peptides or transmembrane segments') and adds no syntax, defaults, or constraints beyond the schema. Baseline 3 applies because the schema carries the parameter semantics.

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 states a specific action ('Find') and resource ('signal peptides or transmembrane segments in reviewed human UniProt') plus a discriminating criterion ('that a sequence predictor contradicts'). It does not name sibling tools such as protein_signal_peptide or protein_topology, so an agent cannot tell from the description alone why it should choose this discovery tool over those single-protein predictors.

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?

No explicit when-to-use, when-not-to-use, or alternative-tool guidance is provided. The narrow scope implies a discordance-discovery use case, but the agent is left to infer it without any statement about when this tool is preferable to protein_signal_peptide or protein_topology.

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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