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pylon_create_ticket_form

Create customizable ticket submission forms to collect specific information for different support request types like bug reports, feature requests, or billing questions.

Instructions

Create a new ticket submission form for customers. Use this to customize what information customers provide when creating different types of support requests (bug reports, feature requests, billing questions).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesForm name that describes its purpose. Examples: "Bug Report Form", "Billing Inquiry", "Feature Request", "Technical Support"
descriptionNoDescription shown to customers explaining when to use this form. Example: "Use this form to report bugs or technical issues with our software."
fieldsYesArray of form field objects defining what information to collect. Example: [{"type": "text", "name": "summary", "required": true}, {"type": "textarea", "name": "steps_to_reproduce"}, {"type": "select", "name": "browser", "options": ["Chrome", "Firefox", "Safari"]}]
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. While it states this is a creation tool ('Create a new ticket submission form'), it doesn't disclose important behavioral traits such as required permissions, whether this operation is idempotent, what happens on failure, or what the expected response format might be. For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.

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 efficiently structured in two sentences with zero waste. The first sentence states the core purpose, and the second sentence provides specific usage context with concrete examples. Every sentence earns its place by adding distinct value.

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?

Given this is a creation/mutation tool with no annotations and no output schema, the description provides adequate purpose and usage context but lacks important behavioral information about permissions, error handling, and response format. The 100% schema coverage helps with parameter understanding, but the overall context remains incomplete for a tool that modifies system state.

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?

The input schema has 100% description coverage, providing detailed documentation for all three parameters. The description adds no additional parameter semantics beyond what's already in the schema. According to the scoring rules, when schema_description_coverage is high (>80%), the baseline score is 3 even with no parameter information in the description.

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 ('Create a new ticket submission form') and resource ('for customers'), with explicit differentiation from sibling tools like 'pylon_create_issue' or 'pylon_create_contact' by focusing on form customization for support requests. It provides concrete examples of form types (bug reports, feature requests, billing questions) that establish its distinct purpose.

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

Usage Guidelines4/5

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 ('to customize what information customers provide when creating different types of support requests') and provides examples of those request types. However, it doesn't mention when NOT to use it or name specific alternatives among the sibling tools, such as when to use 'pylon_create_issue' directly instead of creating a form.

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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