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. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds behavioral detail beyond annotations: 'The row is deactivated (not deleted) so its historical events stay available via recent_alerts.' Annotations already indicate non-destructive and idempotent, but this clarifies the deactivation behavior.
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, front-loaded with the verb, and contains no unnecessary words. 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 simple tool with one parameter and no output schema, the description fully explains the behavior (deactivation), ownership enforcement, and side effects (historical events available). No gaps.
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?
Schema coverage is 100% with a description for 'id' as 'Subscription id (uuid) returned by subscribe.' The description mentions 'by id' and ownership enforcement, adding context but not significantly new meaning beyond the schema.
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 starts with 'Cancel a subscription by id' which is a clear verb+resource. It distinguishes from siblings like 'subscribe' and 'list_subscriptions' by specifying cancellation.
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 states 'Ownership is enforced — you can only cancel your own subscriptions,' providing a clear usage condition. It implies when to use (if you own the subscription) but doesn't explicitly state alternatives or when not to use.
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 clearly distinct purposes, but the three ask_pipeworx variants (standard, beta, grounded) share similar routing and could cause confusion for an agent. The memory tools and novelty tool are distinct. Overall, ambiguity is low.
Tool names follow a consistent snake_case verb_noun pattern (e.g., ask_pipeworx, compare_entities, subscribe). Minor deviations like 'search_within' and 'magic_8_ball_ask' do not break the pattern. High consistency.
With 32 tools, the server is on the heavier side for a single MCP server. However, given the broad domain coverage (financials, economics, prediction markets, etc.), each tool serves a distinct purpose. Bordering on too many, but justified by scope.
The tool surface covers a comprehensive range of data research operations: querying, deep research, entity profiling, comparisons, discovery, subscriptions, alerts, claim validation, and prediction market analysis. Minor gaps exist (no data modification tools), but they are out of scope for a query-oriented server.