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?
Beyond annotations (mutation, idempotent, non-destructive), the description adds concrete behavioral details: ownership enforcement, deactivation rather than deletion, and the impact on recent_alerts. These details are not present in annotations and greatly improve the agent's understanding of the tool's side effects.
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 only two sentences, with the action front-loaded and the key behavioral nuance in the second sentence. Every word earns its place with no fluff or repetition.
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 single-parameter mutation tool with annotations and no output schema, the description is fully sufficient: it covers the action, ownership constraint, lifecycle consequence, and points to a related tool. Missing explicit error handling is acceptable given the tool's simplicity.
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 fully documents the single parameter (subscription id returned by subscribe), and the description adds no further parameter-specific details. This meets the baseline for high schema coverage, but the description does not elevate parameter understanding 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 uses a specific verb and resource ('Cancel a subscription by id') and clearly distinguishes from siblings by noting ownership enforcement and deactivation rather than deletion. This makes its purpose unambiguous and differentiates it from subscribe, list_subscriptions, and recent_alerts.
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 implies when to use it: to cancel a subscription while preserving historical events via recent_alerts. It also notes the ownership restriction, but it does not explicitly state when not to use it or name alternatives, so it falls short of fully explicit guidance.
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.
Many tools have detailed, differentiated roles, but there are several overlapping clusters: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all answer natural-language data questions, and ask_pipeworx_beta is currently identical to ask_pipeworx. Onboarding/discovery and Polymarket edge tools also blur together, so an agent can easily select the wrong entry point.
Names are uniformly snake_case and readable, with coherent subfamilies like ask_pipeworx*, polymarket_*, and list_*. But conventions are mixed across the set: bare verbs (remember, forget, subscribe), noun phrases (entity_profile, recent_changes), and adjective-led names (recent_alerts) exist alongside verb_noun names, so there is no consistent pattern.
35 tools is already in the 'too many' range, and only four (get_exercise, list_exercises, list_equipment, list_muscles) belong to a wger fitness server. The remaining ~31 tools are unrelated Pipeworx/prediction-market/memory utilities, making the count inappropriate for the apparent domain.
As a wger fitness server, the surface is a read-only reference slice: exercise, equipment, and muscle lookups, with no workout routine management, user data, or create/update/delete operations for any wger resource. Even ignoring the unrelated Pipeworx tools, the fitness domain has severe gaps that would block most real usage.