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 important behavioral details beyond annotations: ownership enforcement, deactivation vs deletion, and historical event retention. No contradiction with annotations (idempotentHint=true aligns with deactivation).
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?
Three informative sentences with no fluff. The first sentence front-loads the action, and each subsequent sentence adds value without redundancy.
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 covers the key behavioral aspects (ownership, deactivation, historical availability). Missing error-handling details (e.g., invalid id) are minor given the tool's straightforward nature.
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%, and the schema already describes `id` as a subscription uuid from subscribe. The description does not add further parameter details beyond what the schema provides, so baseline score applies.
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 uses a specific verb ('Cancel') and resource ('subscription'), clearly stating the action and scope (by id, ownership enforced). It effectively distinguishes the tool from siblings like `subscribe` and `list_subscriptions`.
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 clear context: only cancel your own subscriptions and the effect on historical events. While it lacks explicit comparisons to alternatives, the ownership note offers practical guidance for when to use the tool.
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.
Several tools have overlapping purposes (e.g., ask_pipeworx, ask_pipeworx_grounded, deep_research all answer questions; entity_profile, compare_entities, recent_changes all cover company data). Descriptions provide distinctions, but an agent can easily misselect, especially between the Pipeworx query tools.
Tool names follow mixed conventions: some use verb_noun (list_subscriptions, unsubscribe), others use descriptive phrases (ai_visibility_check, polymarket_arbitrage) or nouns (deep_research, entity_profile). No consistent pattern, making it harder to predict tool names.
With 32 tools covering diverse domains (data lookups, prediction markets, memory, subscriptions), the server feels overloaded. The scope would be better served by splitting into smaller, focused servers (e.g., data query, prediction market, memory). Many tools are peripheral to a core purpose.
The tool surface is fairly comprehensive within its domains: CRUD for memory (remember/recall/forget), subscription management, extensive data query options, and prediction market analysis. Minor gaps exist (no update memory, no direct trading), but agents can work around them.