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JobMojito

by com.jobmojito

List merchants you can act as

list_my_merchants
Read-onlyIdempotent

FALLBACK merchant list for clients WITHOUT UI support.

Do NOT use this to choose or switch merchants when a UI is available — call jobmojito_configuration instead (it renders an interactive picker), and do not hand-format a merchant list as text. Use this tool only when the client cannot render MCP App UI. Returns the user's own account plus any sub-merchants; after a pick, pass merchant_id=<chosen id> on subsequent calls (OMIT for the own account).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
searchNoOptional case-insensitive filter on sub-merchant name.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint true and destructiveHint false. The description adds behavioral context: it is a fallback, returns own account plus sub-merchants, and advises how to use the result. No contradictions, and the extra context is helpful, though it doesn't detail rate limits or authentication.

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 concise, using three sentences that front-load the key purpose ('FALLBACK merchant list') and then efficiently cover usage, return content, and follow-up actions. No unnecessary verbiage.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one optional parameter, output schema present), the description is complete: it explains purpose, when to use, what it returns, and how to use the output. The presence of an output schema relieves the need for return value details.

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?

Schema coverage is 100% with one parameter described. The description does not add new semantic information beyond the schema's parameter description; it merely restates 'sub-merchant name' implicitly. Baseline 3 is appropriate.

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 tool's purpose: a fallback merchant list for clients without UI support. It explicitly distinguishes from the interactive picker (jobmojito_configuration) and implies differentiation from list_sub_merchants by indicating it returns both own account and sub-merchants.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit guidance on when to use (only when client cannot render UI), when not to use (when UI is available, use jobmojito_configuration instead), and what not to do (do not hand-format as text). Also provides usage instructions for the returned merchant IDs.

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

A3.6/5.0
Disambiguation4/5

Most tools target distinct resources and actions, with clear category prefixes like [Interviews], [Results], and [Admin]. A few pairs could be confused—create_interview vs. create_interview_from_questions and update_interview vs. set_interview_state—but the descriptions do enough to separate them.

Naming Consistency4/5

The overwhelming majority follow a consistent verb_noun pattern: create_*, get_*, list_*, update_*, generate_*. The main deviation is jobmojito_configuration, which is a noun phrase rather than an action verb, and a few longer names like request_another_interview_attempt break the clean pattern slightly.

Tool Count2/5

With 29 tools, this server is above the 25+ threshold and places a significant navigation burden on an agent. The tools are organized into coherent domains, but several admin/merchant and results tools could likely be consolidated.

Completeness3/5

The core interview lifecycle is well covered: create, read, update, list, state changes, result retrieval, and report generation. However, there are notable gaps such as no delete operations for interviews or catalogue directories, no candidate management beyond listing/registration, and no explicit result-decision tool.

Resources