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Create Workflow Agent

create_workflow_agent

Create a reusable AI agent for the authenticated business. Describe the agent's duties; LocalTry writes and saves its tenant-scoped instruction, then makes the agent available in Flow Studio.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
dutiesYes
taglineNo
categoryNogrowth

Schema Changelog

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

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations only mark the operation as non-read-only and non-destructive. The description usefully adds the write-and-save behavior ('LocalTry writes and saves its tenant-scoped instruction') and the visibility outcome ('makes the agent available in Flow Studio'). No contradiction with annotations.

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 tightly written sentences, with the core purpose front-loaded and the behavioral detail in the second sentence. Every clause adds information; there is no boilerplate.

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?

The description covers the creation flow and the final destination (Flow Studio), which is the key outcome an agent needs. However, there is no output schema and no mention of what the call returns, and optional parameters are left unexplained, making the context slightly incomplete for a 4-parameter creation tool.

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

Parameters2/5

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

With no schema-level descriptions, the description must carry parameter semantics. It clarifies that `duties` becomes the tenant-scoped instruction, and 'Create ... agent' implies `name`, but it gives no semantic help for `tagline` or `category` beyond their raw enum/default values. This only partially compensates for 0% schema coverage.

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 opens with a specific verb and resource: 'Create a reusable AI agent for the authenticated business.' It also names the deliverable (Flow Studio availability), which distinguishes it from sibling tools like create_or_update_crm_record or run_workflow. There is no ambiguity about what action the tool performs.

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?

It provides clear context for when to use the tool: whenever a reusable, tenant-scoped agent needs to be created for the current business. It does not explicitly contrast with alternatives or state when not to use it, so it stops short of a 5.

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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TDQS

B3.4/5.0
Disambiguation2/5

Several tools overlap in purpose: get_workspace_overview and search_localtry_features both return feature/capability catalogs, and get_workspace_customization_status/list_workspace_versions overlap with customization history. run_localtry_command also acts as a generic catch-all that could subsume most of the specific action tools, making selection ambiguous.

Naming Consistency4/5

Most tools follow a clear verb_noun pattern (get_*, search_*, create_*, run_*, list_*, restore_*, request_*). Minor deviations like create_or_update_crm_record and run_localtry_command introduce slight inconsistency, but the overall convention is predictable.

Tool Count5/5

With 12 tools, the server is well-scoped for a platform that covers CRM, workflow agents, workspace customization, and feature discovery. Each tool addresses a distinct functional area without excessive fragmentation.

Completeness4/5

The surface covers the main workflows: CRM upsert/search, workflow agent creation and execution, customization request/status/version restore, and feature discovery. Some lifecycle gaps exist (no delete CRM record, no update/delete agent or workflow), but the generic run_localtry_command can partially compensate.