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Joblogic MCP Server and API by Cotlet

Log job in Joblogic

joblogic_log_job
Read-onlyIdempotent

Log job 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?

The annotations already declare readOnlyHint=true, destructiveHint=false and idempotentHint=true, and the description is consistent with them ('opens nothing by itself'). Beyond the annotations it discloses the return shape (step-by-step screens, buttons, fields) and the API-access constraint, which is real added context even without an output schema.

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?

Three sentences, front-loaded with the action and immediately correcting the expectation set by the name. The trailing API-module note is slightly tangential and the 'checked 9 Nov 2026' date is an odd detail, but neither obscures the core message.

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 guidance tool with no output schema, the description covers what it returns, that it performs no side effects, and what to do next. An agent has everything needed to call it and act on the result.

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 takes zero parameters, so there is nothing for the description to disambiguate; the schema is trivially complete. Baseline of 4 applies for a no-parameter tool.

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 states a specific resource (a job in the user's own Joblogic account) and clarifies the surprising behavior implied by the name: it returns step-by-step guidance rather than performing the action, and 'opens nothing by itself'. It does not explicitly contrast itself with the direct-action siblings like joblogic_create_quote, so sibling differentiation is only implied via the handoff to cotlet_browser_*.

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 clear usage context: get instructions here, then execute them with the cotlet_browser_* tools in the Joblogic Cloud Browser. It also explains why this route exists (the official REST API is a paid Marketplace module for developers). It stops short of naming when not to use this tool or which sibling handles the direct-action alternative.

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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