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. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that the row is deactivated not deleted, and historical events remain via 'recent_alerts', which adds value beyond annotations (idempotentHint, destructiveHint). No contradiction with annotations.
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, no filler, front-loaded with the core action, very efficient.
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 good annotations, the description covers purpose, usage constraint, behavioral outcome, and a relevant sibling tool, making it complete.
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%, so the description adds no extra meaning beyond the schema. Baseline of 3 is appropriate.
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', using a specific verb and resource, and distinguishes itself from sibling 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?
Explicitly states ownership enforcement ('you can only cancel your own subscriptions') and the deactivation behavior, which guides when to use this tool. Does not explicitly contrast with other tools but the context is clear.
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.
Tools are individually well-described, but there is overlapping functionality among ask_pipeworx, ask_pipeworx_grounded, and deep_research, as well as multiple prediction market tools. The detailed descriptions help, but the number of similar tools creates some ambiguity.
Tool names follow a consistent snake_case pattern with descriptive prefixes (e.g., ask_pipeworx, entity_profile, polymarket_edges). There are minor deviations like 'deep_research' vs 'bet_research' but overall the naming is predictable and clear.
The server is named 'Texas Open Data' but only 3 of 33 tools (datasets, metadata, query) are directly related to Texas open data. The remaining tools cover a much broader domain (Pipeworx ecosystem), making the tool count inappropriate for the stated purpose.
For the stated purpose of Texas Open Data, the tool surface is incomplete—only basic query and metadata capabilities are provided, lacking data management, update, or delete operations. As a general pipeworx server it might be more complete, but the name suggests Texas-specific data.