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jean — Molecular Biology & Genomics

enumerate_protonation_states

Read-only

Enumerate a small molecule's protonation states across a pH window with Dimorphite-DL (Ropp et al. 2019): each ionisable group it recognizes (substructures with pKa means and spreads taken from measured pKa values) is kept protonated, deprotonated or both, and every combination is returned as SMILES. Reproduces Dimorphite-DL 2.1.0, including that it neutralizes charged groups first and keeps only the part it neutralized.

Input Schema

TableJSON 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.
ph_maxNoupper end of the pH window.
ph_minNolower end of the pH window.
_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.
moleculeYesthe structure: SMILES or a molfile.
precisionNohow many standard deviations of each group's pKa widen its window, 0–10.
max_variantsNostop enumerating past this many states (later groups are then not visited).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
sitesYesper ionisable site: Dimorphite name, SMARTS, each pKa (mean, stdev, state) and its atoms on the input (0-based, implicit hydrogens), or null when they do not map
cappedYestrue when the enumeration stopped at max_variants
statesYesevery protonation state as canonical SMILES, sorted
summaryYesthe enumeration in words, generated from this run, with its caveats

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations only declare the read-only, non-destructive safety profile, but the description adds real behavioral context: each group is kept protonated/deprotonated/both and every combination returned, the pKa values are measured-derived, and there is a disclosed quirk that charged groups are neutralized first and only the neutralized part kept. This is meaningful disclosure beyond the annotations, though the max_variants truncation behavior is left to the schema.

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?

Two sentences, front-loaded with the core action and algorithm, and no filler. The parenthetical citation and the 'Reproduces Dimorphite-DL 2.1.0' clause are slightly redundant but defensible as provenance for a reimplementation.

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?

An output schema exists, so return values need not be explained, and the description is complete for the chemistry behavior. The only gaps are the absence of routing guidance versus sibling enumeration tools and the unexplained project/record scaffolding parameters, which the schema covers but the description never ties together.

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 ph_min/ph_max/precision/max_variants are already fully documented in the schema. The description explains the conceptual model behind precision (pKa means and spreads) and the pH window, but adds no new syntax or format detail beyond the structured fields, so the baseline 3 applies.

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 names a specific verb and resource (enumerate protonation states), the algorithm used (Dimorphite-DL), the scope (across a pH window), and the return format (SMILES). It is precise enough that an agent can distinguish it from nearby chemistry tools like canonical_tautomer or generate_conformers, though it does not explicitly name an alternative.

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 implied rather than stated: an agent can infer it is for generating pH-dependent protomers of a small molecule, but there is no explicit when-to-use, when-not-to-use, or named alternative. For a chemistry enumeration tool sitting among tautomer/conformer siblings, that routing guidance would be valuable.

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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