unsubscribeCancel a subscription by id. Ownership is enforced — you can only cancel your own subscriptions. The row is deactivated (not deleted) so its historical events stay available via recent_alerts.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Subscription id (uuid) returned by subscribe. |
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?
Adds significant value beyond annotations: describes deactivation vs deletion, ownership check, and impact on historical data. Annotations only indicate non-destructive and idempotent but not these specifics.
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 sentences, zero waste. Every sentence provides essential information: action, constraint, and side effect.
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?
Completely covers the tool's purpose, behavior, and side effects. Absence of output schema is not an issue as return is implicit. References recent_alerts for related functionality.
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?
Single parameter 'id' is fully described in schema (UUID from subscribe). Description does not add much, but schema coverage is 100%, so baseline 3 is exceeded due to clarity.
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?
Clearly states the action (cancel subscription by id), specifies the resource, and distinguishes from sibling tools like subscribe and list_subscriptions by noting the deactivation behavior.
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?
Explicitly mentions ownership enforcement (only cancel own subscriptions) and notes that historical events remain available via recent_alerts. Does not explicitly state when not to use, but context is clear enough.
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.
Most tools have distinct purposes with detailed descriptions; however, the family of ask_pipeworx tools (beta, grounded) and deep_research could cause selection ambiguity despite clear documentation.
Tool names lack a consistent pattern; they mix imperatives, descriptive nouns, and domain prefixes. While overall readable, the lack of uniformity makes it harder to predict naming conventions.
34 tools is on the higher side but still within reasonable range given the broad scope (data queries, prediction markets, scraping, subscriptions, memory). Each tool appears purposeful, though some consolidation (e.g., ask_pipeworx variants) could reduce count.
The tool set covers a wide range of tasks from data querying to prediction market analysis and entity management. Minor gaps might exist (e.g., no direct social media data), but the overall coverage is extensive and sufficient for the platform's purpose.