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 goes beyond the annotations by revealing that cancellation is a soft delete ('deactivated, not deleted') and that ownership is enforced. It also connects the side effect to recent_alerts, which is valuable behavioral context not present in the annotations or schema.
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, front-loaded with the core action. Every sentence carries essential information without redundancy or fluff.
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?
The description covers purpose, ownership constraint, and the soft-delete behavior. It does not state the return value or error cases, but given the simple single-parameter interface and strong annotations, this is a minor gap. Overall, the agent receives enough to select and invoke the tool correctly.
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 schema already provides a complete description for id ('Subscription id (uuid) returned by subscribe'). The description adds an extra semantic: the id must be a subscription you own. This adds meaning beyond the schema's type and provenance.
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 states a clear, specific action: 'Cancel a subscription by id.' It also distinguishes the tool by adding ownership enforcement and the soft-delete behavior, which sets it apart from related tools 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 implies usage context: use this to cancel a subscription you own, and the deactivation behavior ensures historical events remain available via recent_alerts. It does not explicitly name alternatives or exclusions, but the ownership and soft-delete details provide sufficient usage 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.
Several tool clusters overlap heavily: ask_pipeworx and ask_pipeworx_beta are documented as functionally identical right now, and polymarket_arbitrage / polymarket_edges / polymarket_edge_tracker all surface trade opportunities with similar outputs. discover_tools and suggest_questions also cover similar 'what can I do' territory.
All names are snake_case and many use verb_noun (query_layer, resolve_entity, generate_llms_txt), but a large minority use noun/adjective phrases (layer_info, recent_changes, polymarket_edges, bet_research) or bare verbs (remember, forget, recall). The pattern is readable but not fully predictable.
34 tools is over the 25-tool threshold and deeply mismatched with the server name: only 3 of them (search_datasets, query_layer, layer_info) relate to ArcGIS Albuquerque. Most of the surface is a general-purpose Pipeworx data platform, making the set bloated and unfocused.
The advertised ArcGIS domain has only search-schema-query coverage: there is no way to list all datasets, apply spatial filters, or get service-level metadata. The Pipeworx half is feature-rich, but for the server as titled the tool surface has significant gaps and a large amount of irrelevant functionality.