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author_agentic_workflow

Turn a natural-language prompt into a validated agentic workflow artifact. Publish after validation when requested, or keep a zero-write local draft to avoid unintended publication.

Instructions

Create an agentic workflow artifact from a prompt.

Args: prompt: Natural-language workflow request. name: Optional workflow display name. workflow_type: Optional stable workflow type/key. preferred_domains: Optional comma-separated domains such as crm,finance,communications. publish: When true, publish after validation passes. Defaults to a zero-write local draft so an agent never publishes implicitly.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo
promptYes
publishNo
workflow_typeNo
preferred_domainsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Addedv0.1.1

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the burden of behavioral disclosure, and it does so well for the most important side effect: 'publish' defaults to a zero-write local draft so an agent never publishes implicitly, and publishing only happens after validation passes. It could add details about validation failures or artifact visibility, but the core write/implicit-publish safety behavior is explicit.

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 compact and front-loaded with the core action, followed by a tight Args list where each line adds distinct value. There is no filler or duplication of schema defaults.

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 creation tool with an output schema and five inputs fully explained, the description is largely complete. It covers the key behavioral context (no implicit publishing, validation gate) and all parameter semantics; the main gaps are lack of alternative-tool routing and explicit post-creation expectations, but those are secondary given the output schema.

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

Parameters5/5

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

Schema description coverage is 0%, and the description fully compensates by explaining every parameter: prompt is a natural-language request, workflow_type is a stable key, preferred_domains is comma-separated with concrete examples, and publish is defined with its default behavior. This is exactly the semantic detail an agent needs beyond the bare schema.

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 opens with a specific verb and resource: 'Create an agentic workflow artifact from a prompt.' It clearly identifies what is produced and the input source, but it does not explicitly differentiate this tool from nearby siblings like author_workflow_trigger or compile_business_workflow.

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?

There is no guidance on when to prefer this tool over alternatives, no prerequisites, and no exclusions. The publish parameter doc hints at safe usage, but the description never says 'use this when...' or names sibling tools that should be used instead.

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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