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create_form_submission

Creates a form submission to capture lead details and custom answers, and optionally creates a pipeline opportunity by providing a stage name.

Instructions

Create a new form submission with lead information and custom answers. Can optionally create a pipeline opportunity by providing pipelineStageName.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNoCity
roleNoLead's role/title
emailNoLead's email address
notesNoGeneral notes about the submission
phoneNoLead's phone number
postalNoPostal/ZIP code
answersNoArray of structured question/answer objects for custom form fields
countryNoCountry
websiteNoLead's website URL
address1NoStreet address line 1
address2NoStreet address line 2
formNameNoAssociate the submission with an existing form template for reporting purposes
lastNameNoLead's last name
localityNoState/Province/Region
firstNameNoLead's first name
sourceUrlNoSource URL where the form was submitted
leadSourceNoLead source tracking
businessNameNoLead's business/company name
pipelineStageNameNoIf provided, automatically creates an Opportunity in your pipeline. Must match exactly one of your pipeline stage names
Behavior3/5

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

With no annotations, the description must convey behavioral traits. It discloses the core action and optional opportunity creation, but lacks details on side effects (e.g., idempotency, auth requirements, data persistence, or what happens if pipelineStageName doesn't match). The parameter note about exact matching is only in the schema, not the description.

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?

Two sentences, no wasted words. Front-loaded with the main purpose, followed by the key optional behavior. Efficient and clear.

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

Completeness2/5

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

Given 19 parameters, no output schema, and no annotations, the description is too brief. It doesn't explain return values, error conditions, prerequisites (e.g., form template or pipeline stages), or how the outputs connect to other entities. Many agent questions would remain unanswered.

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 coverage is 100%, so baseline is 3. The description adds value by grouping parameters under 'lead information' and highlighting the optional pipelineStageName behavior, but does not explain individual parameters beyond what the schema provides.

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 clearly states it creates a form submission with lead info and custom answers, and optionally creates an opportunity. It distinguishes from sibling tools like create_client or create_contact by specifying 'form submission', but could further clarify the typical use case (e.g., web form capture).

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?

The description provides no guidance on when to use this tool versus alternatives like create_contact or create_opportunity. The optional pipeline opportunity is mentioned, but there is no explicit 'when to use' or 'when not to use' advice, leaving the agent to infer context.

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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