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list_draft_prompts

Retrieve all saved draft prompts for a specific company. Provide the company name in kebab-case to access prompts for review and iterative testing.

Instructions

List all saved draft prompts for a specific company

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
company_nameYesCompany name in kebab-case (e.g., 'technical-life-care')
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavior. It implies a read-only list operation but does not mention return format, pagination, or any limitations beyond company scope. The phrase 'all saved draft prompts' adds some context but largely just restates the tool's name.

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 a single, eight-word sentence that immediately states the action and resource. There is no redundancy or extraneous detail, making it highly concise and well-structured.

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?

For a simple list tool with one well-documented parameter, the description conveys the core purpose adequately. However, without an output schema or annotations, the agent is left without details on response structure or behavior, and the description does not address potential limitations or alternatives.

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 provides a thorough description of company_name, including format and example, and schema coverage is 100%. The tool description's mention of 'a specific company' aligns with the parameter but adds no new semantic value, so the baseline of 3 applies.

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 action (List), the resource (saved draft prompts), and the scope (for a specific company). This distinguishes it from sibling tools like list_test_cases and get_draft_prompt, which target different resources.

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 explicit guidance on when to use this tool versus alternatives. It does not mention that get_draft_prompt is for retrieving a single prompt or that save_draft_prompt is for creating them, leaving the agent without clear selection criteria.

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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