TestMyVibes

Publish a new service offering

create_worker_offering

Add a named, priced offering to your worker menu. Customers see name + description + creditsCharged + estDurationHr and pick directly. Worker earns 75% of credits charged (floor-rounded); TMV keeps 25%. Price must be a whole number of credits, ≥ 15. Until your account is uncapped (3 quality-scored jobs, OR 1 four-star+ customer review, OR $100 cleared earnings), the per-offering ceiling is 50 credits.

Input Schema

TableJSON Schema

Name	Required	Description
`name`	Yes
`description`	Yes
`specialties`	No
`estDurationHr`	No
`creditsCharged`	Yes	Whole-number credit price. Floor=15. New-worker ceiling=50.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	No	Tool result payload (JSON object)

TDQS

A4.5/5.0

Behavior5/5

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

The description reveals behavioral traits beyond annotations, such as the earnings split (75% worker, 25% TMV), price constraints (whole number, ≥15), and the ceiling condition for uncapped accounts. This adds significant value without contradicting 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?

The description is concise (three sentences), front-loaded with the core purpose, and every sentence adds necessary information without fluff. It efficiently communicates the tool's usage, constraints, and business rules.

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 complexity (5 parameters, output schema exists), the description covers critical business logic: pricing, earnings split, worker eligibility conditions, and what customers see. This is sufficient for an agent to invoke the tool correctly.

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 description coverage is low (20%), and the description partially compensates by explaining pricing rules for 'creditsCharged' and customer visibility of 'name', 'description', 'creditsCharged', and 'estDurationHr'. However, 'specialties' is left unmentioned, and required parameters like 'name' and 'description' lack detail beyond schema.

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: 'Add a named, priced offering to your worker menu.' It specifies the verb 'Add' and the resource 'offering', distinguishing it from sibling tools like 'list_worker_offerings'.

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?

The description provides clear context on when to use (to publish a service offering) and includes constraints like minimum price and ceiling for new workers. However, it does not explicitly state when not to use or mention alternative tools, losing one point.

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

A3.9/5.0

Disambiguation4/5

The tools cover a wide range of functionalities, but each has a clearly distinct purpose. For example, submit_test, submit_test_batch, submit_combo, and submit_interaction_scene are all different types of submissions with unique parameters. However, the sheer number of tools (43) might cause some initial confusion, but descriptors resolve ambiguity.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case (e.g., list_projects, create_project, get_test_results). The only exception is 'whoami', which is a common idiom and does not break the pattern. Overall, naming is highly predictable.

Tool Count3/5

43 tools is on the high side for a single server. The domain is broad (testing, worker marketplace, credits, cards, feedback, video), so the count is justifiable. However, it borders on being overwhelming, and some tools could be consolidated (e.g., multiple submit_* variants).

Completeness3/5

The tool surface covers core workflows like project creation, test submission, result retrieval, worker management, and credit operations. However, there are gaps: no update or delete for projects, no delete for worker offerings, and no user-facing combo editing (though combos are predefined). These are minor but noticeable.

Resources

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