lemonvite_get_accountUse this when the user asks which Lemonvite account is connected, how many publish credits they have, or how many design generations are left. Read-only.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| Yes | |||
| credits | Yes | ||
| credit_price_display | Yes | ||
| generations_remaining | Yes | Design generations left for lemonvite_generate_design. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint: true, and the description reinforces this with 'Read-only.' It adds useful context about the scope of account information returned (publish credits, design generations), but does not address potential edge cases like missing accounts or authentication failures. The annotation does the heavy lifting, so the description is not underperforming.
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 a single, front-loaded sentence with a clear 'Use this when' trigger, followed by a minimal 'Read-only' note. Every word earns its place, with no redundant information.
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?
With zero parameters, readOnlyHint set, and an output schema present, the description covers what the agent needs to call and interpret results. It does not include edge-case behavior, but for a simple parameterless read operation the description is complete enough.
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?
The tool has zero parameters, and schema description coverage is 100%, so no parameter documentation is required. The description adds value by indicating what the returned account object conveys (credits and generation counts), which is sufficient for a parameterless tool.
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 identifies the tool's purpose by listing the exact user intents it serves (connected account, publish credits, design generations). This distinguishes it from siblings focused on invitations and guests, though it does not explicitly name a sibling alternative.
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?
It explicitly states 'Use this when the user asks...' and specifies the exact queries that trigger this tool. It lacks explicit exclusions or alternative tool references, but the trigger conditions are clear and sufficient for the agent to route correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.