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 significant value beyond annotations by explaining the behavioral trait: the row is deactivated, not deleted, preserving historical events via recent_alerts. It also reinforces the ownership check. Annotations only indicate readOnly=false, destructive=false, but the description fills in the specific mutation behavior.
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 consists of two concise, front-loaded sentences. Every sentence provides essential information: the action, ownership constraint, and the effect on the row. No extraneous words.
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 is complete. It covers purpose, usage constraint, and behavioral outcome. No additional context is necessary.
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 describes the 'id' parameter as a UUID returned by subscribe, with 100% coverage. The description adds no further parameter details beyond mentioning 'by id.' With full schema coverage, the baseline score is 3.
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 'Cancel a subscription by id,' specifying the verb (cancel) and the resource (subscription). It distinguishes itself from sibling tools like 'subscribe' and 'list_subscriptions' by focusing on cancellation.
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 for when to use the tool by noting ownership enforcement: 'you can only cancel your own subscriptions.' It also explains the consequence of deactivation versus deletion. However, it does not explicitly list conditions where the tool should not be used or suggest alternatives.
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: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical (beta is currently identical to ask_pipeworx), and deep_research and validate_claim also overlap with the ask_pipeworx family. The Polymarket tools are more distinct, but the query family creates real ambiguity.
Tool names mix leading verbs (ask_, compare_, resolve_, scan_) with leading nouns (entity_profile, recent_changes, hnb_currency_rate) and there are multiple subfamily prefixes (ask_pipeworx_*, polymarket_*, hnb_*). All are snake_case, but no consistent verb_noun or noun pattern is followed.
33 tools is well above the 25+ threshold, and the server name ('Hnb Hr') implies a narrow Croatian banking scope while the majority of tools are for a broad data research platform. Many meta-tools (discover_tools, suggest_questions, pipeworx_feedback, pipeworx_trending) inflate the count beyond what the apparent purpose needs.
The HNB currency functionality is complete (single and all rates, historical and latest), and the broader data platform offers good coverage via the ask_pipeworx router, subscriptions, and memory tools. However, there are gaps (no direct HNB news or historical archive tool, patents soft-fail, and out-of-domain tools like generate_llms_txt), and the mismatch between server name and content leaves the surface feeling incomplete.