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submit_double_ended_ts_search_workflow

Find transition states between known reactant and product molecules using double-ended search algorithms for chemical reaction analysis.

Instructions

Submit a double-ended transition state search workflow using Rowan v2 API.

IMPORTANT: Reactant and product MUST have the exact same number and types of atoms, just in different arrangements (e.g., C#N and [C-]#[NH+] both have 1C, 1N, 1H). The workflow will fail if atom counts don't match.

Args: reactant: Reactant molecule as SMILES string. Must have same atoms as product. product: Product molecule as SMILES string. Must have same atoms as reactant. calculation_settings: JSON string for calculation settings. Empty string uses defaults. search_settings: JSON string for TS search configuration. Empty string uses defaults. optimize_inputs: Whether to optimize reactant/product before search (default: False) optimize_ts: Whether to optimize found transition state (default: True) 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.

Locates transition states connecting known reactant and product structures using double-ended search algorithms. More robust than single-ended TS optimization when both endpoints are known.

Returns: Workflow object representing the submitted workflow

Examples: # HCN isomerization - both have 1C, 1N, 1H ✓ result = submit_double_ended_ts_search_workflow( reactant="C#N", # HCN (hydrogen cyanide) product="[C-]#[NH+]", # CNH (isocyanic acid tautomer) optimize_inputs=True, optimize_ts=True, name="H-C≡N Isomerization" )

# Keto-enol tautomerization - both have C3H6O ✓
result = submit_double_ended_ts_search_workflow(
    reactant="CC(=O)C",          # Acetone (keto form)
    product="CC(O)=C",           # Prop-1-en-2-ol (enol form)
    name="Keto-Enol Tautomerization"
)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
reactantYesReactant SMILES string (e.g., 'C#N'). MUST have same atom count as product
productYesProduct SMILES string (e.g., '[C-]#[NH+]'). MUST have same atom count as reactant
calculation_settingsNoJSON string for calculation settings (method, basis set, etc.). Empty for defaults
search_settingsNoJSON string for TS search settings (e.g., convergence criteria). Empty for defaults
optimize_inputsNoWhether to optimize reactant and product geometries before TS search
optimize_tsNoWhether to optimize the transition state after finding it
nameNoWorkflow name for identification and trackingDouble-Ended TS Search 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 full burden and does well by disclosing critical failure conditions ('workflow will fail if atom counts don't match'), computational cost implications ('Maximum credits to spend'), and workflow organization behavior ('folder to organize this workflow'). It doesn't fully cover rate limits or detailed error responses, but provides substantial behavioral context.

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?

The description is well-structured with clear sections (purpose, constraints, args, returns, examples) and every sentence adds value. It front-loads the most critical information (purpose and constraints) and uses examples efficiently to illustrate complex parameter relationships without redundancy.

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 complex 9-parameter workflow submission tool with no annotations and no output schema, the description provides substantial context including purpose, constraints, parameter relationships, and return value explanation. It could benefit from more detail about the returned 'Workflow object' structure, but otherwise covers most essential aspects given the complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema description coverage, the baseline is 3, but the description adds significant value by explaining the critical relationship between reactant and product parameters ('MUST have same atom count'), providing context for JSON settings parameters, and clarifying default behaviors. The examples further illustrate parameter usage beyond schema descriptions.

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 double-ended transition state search workflow') and resource ('using Rowan v2 API'). It distinguishes from sibling tools by focusing on transition state searches between reactant and product molecules, unlike other workflow types like docking or ADMET.

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

Usage Guidelines5/5

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

The description explicitly states when to use this tool ('More robust than single-ended TS optimization when both endpoints are known') and provides critical constraints ('Reactant and product MUST have the exact same number and types of atoms'). It also distinguishes from alternatives by mentioning single-ended TS optimization as a comparison point.

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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