Check Subscription Status
check-subscriptionCheck the status of a JobDoneBot checkout session.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| session_id | Yes | Stripe checkout session ID (cs_xxx) |
check-subscriptionCheck the status of a JobDoneBot checkout session.
| Name | Required | Description | Default |
|---|---|---|---|
| session_id | Yes | Stripe checkout session ID (cs_xxx) |
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?
With no annotations, the description carries full burden for behavioral disclosure. It implies a read-only check but does not explicitly state that it's safe, does not describe possible status values or side effects, and gives no information about return behavior, all of which are critical for an agent.
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 that directly states the purpose with no redundant phrasing. It is appropriately sized for a simple tool.
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?
There is no output schema, so the description should explain return values or status semantics, but it does not. The meaning of 'status' for a checkout session is left undefined, and there's no mention of errors or edge cases, making the tool incomplete for an agent to invoke confidently.
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 input schema covers 100% of the single parameter (session_id) with a clear description ('Stripe checkout session ID (cs_xxx)'). The tool description adds no further parameter details, but the baseline of 3 applies due to high schema coverage.
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 a specific action ('Check') and resource ('JobDoneBot checkout session'), which is unambiguous. It distinguishes from siblings by focusing on session status rather than subscription purchase, though it doesn't explicitly name alternatives.
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 provides no guidance on when to use this tool versus alternatives, no prerequisites, and no context such as typical scenarios. It only states what the tool does, leaving usage entirely to the agent's inference.
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.
Multiple tools have overlapping purposes, such as bg-remover, bg-remover-pro, pro-matting, and takumi all performing background removal, and upscaler/upscaler-pro being redundant. With 202 tools, an agent may easily select the wrong one despite detailed descriptions.
Most tools use a consistent kebab-case format with descriptive names like pdf-compress, image-resizer, and tax-return-calc. Exceptions like 'takumi', 'pro-matting', and '-pro' suffixes (bg-remover-pro, upscaler-pro) are minor deviations relative to the total.
202 tools is an extreme mismatch for an MCP server, far exceeding the typical 3-15 well-scoped range. The sheer volume makes it unwieldy for an agent to efficiently navigate and select the right tool.
The tool set provides extensive coverage across many domains, including PDF operations (20+ tools), image editing, financial calculations, e-commerce fee estimation, and YouTube utilities. Minor gaps exist in cross-tool integration, but the breadth is highly comprehensive for the apparent purpose.