chat_pass
Passe mensal do chat ($0.10 / 30 dias). Sem pagamento → 402.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Passe mensal do chat ($0.10 / 30 dias). Sem pagamento → 402.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 the burden of behavior disclosure. It does add useful behavioral context: the pass costs $0.10 per 30 days and a missing payment results in HTTP 402. However, it does not describe what happens on successful payment, whether this creates a subscription, or what response/side effects the agent should expect.
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?
Two short, dense sentences convey price, duration, and a key failure behavior. There is no filler or repetition, and the core information is front-loaded.
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 pass/payment-related tool with no annotations and no output schema, the description is too thin. It does not clarify whether the tool is a purchase action or a status check, what a successful call returns, what authentication is needed, or how it relates to the sibling billing and nsfw pass tools.
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 has zero parameters, so there are no parameter semantics to document. The description correctly focuses on the tool's behavior and pricing rather than inventing parameter explanations, matching the baseline for zero-parameter tools.
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 identifies the resource as a monthly chat pass and gives price/duration, but it lacks a concrete verb. It does not clearly say whether the tool buys, activates, checks, or renews the pass, and it does not distinguish itself from the sibling nsfw_pass_buy/nsfw_pass_status pair.
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?
There is no guidance on when to call this tool or when to prefer a sibling such as nsfw_pass_buy, nsfw_pass_status, or billing. The intended trigger—whether a user wants to purchase a pass or check access—is left entirely to 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.
Each tool addresses a distinct resource/action: favorites vs. history vs. watch recording are clearly separate, and the NSFW consent/pass tools are unambiguous. Even closely related tools like 'get_channel', 'get_channel_guide', and 'legacy_stream' serve different purposes. No two tools appear to do the same thing.
Most tools follow a verb_noun pattern (get_, list_, create_, add_, remove_, etc.) with clear conventions. A few exceptions exist like 'billing', 'geo', 'health', and 'me', which are nouns and break the pattern slightly, but the overall style is predictable and readable.
With 47 tools, the server is far beyond the typical well-scoped range (3-15). While the API covers a broad domain (auth, catalog, chat, comments, billing, NSFW), this many tools would be better split into smaller, focused servers. The count feels bloated and could overwhelm an agent.
The tool surface is quite comprehensive for a streaming service: it includes auth, user preferences, favorites, history, catalog search, channel details, comments, chat, NSFW consent/passes, billing, and reporting. Minor gaps exist (e.g., no update/delete for categories/groups, no comment editing), but these are not critical dead ends.