get_credit_balanceGet the current account's credit balance. Returns total valid credits, raw batches, and a warning flag if the balance is below the threshold a typical test costs.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| result | No | Tool result payload (JSON object) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the agent knows it's a safe read. The description adds value by detailing the return components (total valid credits, raw batches, warning flag) and the condition for the warning flag, providing behavioral context beyond 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, with the first sentence front-loading the purpose. It contains no filler words and every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a no-parameter tool that returns credit balance info, the description is fully adequate. It explains what is returned and mentions the threshold condition. Given the presence of an output schema (not shown), the description does not need to elaborate on the return format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so the description does not need to add parameter semantics. With zero parameters, the baseline is 4. The description focuses on the output details, which is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets the credit balance for the current account. It uses a specific verb+resource pattern and distinguishes itself from the sibling tool 'top_up_credits' which performs a different operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions a threshold condition ('below the threshold a typical test costs') which hints at when checking is useful, but does not explicitly state when to use this tool versus alternatives or when not to use it. Some guidance is implied by context with 'top_up_credits'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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).
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.