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submit_solubility_workflow

Predict solubility (log S) of molecules in multiple solvents at various temperatures using machine learning models via Rowan's computational chemistry platform.

Instructions

Submit a solubility prediction workflow using Rowan v2 API.

Args: initial_smiles: SMILES string of the molecule for solubility prediction solvents: JSON string list of solvents as SMILES or names (e.g., '["water", "ethanol", "CCO"]'). Empty string uses defaults temperatures: JSON string list of temperatures in Kelvin (e.g., '[298.15, 310.15]'). Empty string uses default range name: Workflow name for identification and tracking folder_uuid: UUID of folder to organize this workflow. Empty string uses default folder. max_credits: Maximum credits to spend on this calculation. 0 for no limit.

Predicts solubility (log S) of a molecule in multiple solvents at various temperatures using machine learning models.

Returns: Workflow object representing the submitted workflow

Example: # Basic solubility prediction result = submit_solubility_workflow( initial_smiles="CC(=O)Nc1ccc(O)cc1", solvents='["water", "ethanol"]', temperatures='[298.15, 310.15]' )

# With SMILES solvents
result = submit_solubility_workflow(
    initial_smiles="CC(=O)O",
    solvents='["O", "CCO", "CCCCCC"]',
    temperatures='[273.15, 298.15, 323.15]'
)

This workflow can take 5 minutes to complete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
initial_smilesYesSMILES string of the molecule for solubility prediction
solventsNoJSON string list of solvents as SMILES or names (e.g., '["water", "ethanol", "CCO"]'). Empty string uses defaults
temperaturesNoJSON string list of temperatures in Kelvin (e.g., '[298.15, 310.15]'). Empty string uses default range
nameNoWorkflow name for identification and trackingSolubility Workflow
folder_uuidNoUUID of folder to organize this workflow. Empty string uses default folder
max_creditsNoMaximum credits to spend on this calculation. 0 for no limit
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: the workflow 'can take 5 minutes to complete' (indicating potential latency), and it explains default behaviors for empty strings in parameters. However, it does not mention error handling, rate limits, or authentication needs, leaving some gaps.

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 well-structured with clear sections (purpose, args, returns, examples, note on timing). It is front-loaded with the core purpose and includes useful examples. Some redundancy exists (e.g., repeating parameter info from schema), but overall it is efficient and informative.

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?

Given the complexity (6 parameters, no output schema, no annotations), the description is fairly complete. It covers purpose, parameters, returns, examples, and timing. However, it lacks details on output format (beyond 'Workflow object') and error cases, which could be improved for full contextual understanding.

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 all parameters thoroughly. The description adds minimal value beyond the schema, such as clarifying that solvents can be SMILES or names and providing example JSON strings. This meets the baseline for high schema coverage without significant enhancement.

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?

The description clearly states the specific action ('Submit a solubility prediction workflow') and resource ('using Rowan v2 API'), with a detailed explanation of what it predicts ('solubility (log S) of a molecule in multiple solvents at various temperatures using machine learning models'). It distinguishes from siblings like 'submit_admet_workflow' or 'submit_docking_workflow' by focusing on solubility prediction.

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?

The description implies usage for solubility prediction workflows but does not explicitly state when to use this tool versus alternatives like 'submit_basic_calculation_workflow' or other workflow tools. It provides context through examples but lacks explicit guidance on when-not-to-use or direct alternatives for solubility tasks.

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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