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Joblogic MCP Server and API by Cotlet

Create quote in Joblogic

joblogic_create_quote
Read-onlyIdempotent

Create quote in the user's own Joblogic account from ChatGPT, Claude or any AI agent. Returns how to do it in Joblogic step by step (screens, buttons, fields) and opens nothing by itself; then do it with the cotlet_browser_* tools in the user's Joblogic Cloud Browser. Joblogic's official API: Joblogic has a documented REST API, but it is a paid "API Access" Marketplace module meant for developers (checked 9 Nov 2026).

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already mark it read-only, non-destructive, idempotent, and closed-world. The description adds useful behavior beyond those annotations: it opens nothing by itself, returns step-by-step instructions, and notes that Joblogic's official API is a paid developer module. It does not detail auth or rate limits, but that bar is lower given the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences and front-loads the workflow, with no repeated filler. The API note is relevant context but somewhat tangential to the immediate call, keeping it from being maximally tight.

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 zero-parameter read-only guide tool with no output schema, the description explains the return content (step-by-step screens, buttons, fields), states that it takes no action itself, and names the next tool family to use. It could explicitly mention prerequisites such as being logged into Joblogic, but it is otherwise complete enough.

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

Parameters4/5

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

The tool has zero parameters, so the baseline is 4. The description adds no parameter semantics, but none are needed for this empty 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 specifies the resource (a quote in the user's own Joblogic account) and clarifies that the tool returns step-by-step instructions rather than performing the creation, then points to cotlet_browser_* for execution. This distinguishes it from browser automation siblings, though the opening 'Create quote' phrasing can initially suggest a write operation.

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 gives a clear workflow: call this to get the Joblogic screens, buttons, and fields, then use cotlet_browser_* tools in the user's Joblogic Cloud Browser to perform the action. It does not state when not to use it or explicitly compare with cotlet_app_guide, so it falls 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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