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 valuable behavioral detail beyond the annotations: the row is deactivated rather than deleted, and historical events remain available via recent_alerts. It also discloses ownership enforcement. This goes beyond the annotations' readOnly/destructive hints without contradicting them.
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 concise sentences, front-loaded with the primary action and immediately followed by key behavioral caveats. Every sentence adds meaningful information 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, single-parameter mutation tool, the description covers the essential outcome (deactivation vs deletion) and future availability of data. It lacks an explicit success response format, but the absence of an output schema and the tool's simplicity make this acceptable.
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 already provides full coverage (100%) for the single 'id' parameter, including that it is a UUID returned by subscribe. The description adds only the ownership constraint, which is contextual rather than parameter-specific, so it does not significantly augment 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 clearly states the action ('Cancel a subscription by id') with a specific verb and resource. It distinguishes itself from sibling tools like 'subscribe' and 'list_subscriptions' by focusing on cancellation using a subscription id.
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: it requires a subscription id and enforces ownership, implying use after subscribing. It does not explicitly name alternatives like 'list_subscriptions', but the purpose is unmistakable and the ownership constraint clarifies appropriate 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.
Each tool has a clearly distinct purpose, with detailed descriptions that specify when to use each. Even overlapping functions like ask_pipeworx varieties are well-differentiated by mode (casual vs grounded vs multi-source).
Most tool names follow a verb_noun snake_case pattern (e.g., query_layer, resolve_entity), but a few deviate with single-word verbs (forget, remember, recall) or noun_noun (layer_info). The pattern is mostly consistent with minor exceptions.
With 33 tools, the count is high and borders on heavy. However, the tools span multiple domains (GIS, financial data, prediction markets, memory, subscriptions), and each serves a unique role, so the count is justifiable but could be streamlined.
The tool set covers a broad range of data access and analysis tasks relevant to the inferred domain of a multi-purpose assistant. While the ArcGIS portion is limited, the overall surface is well-populated with few obvious gaps.