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 annotations already indicate non-destructive (destructiveHint=false) and mutating (readOnlyHint=false), but the description adds valuable context beyond that: the row is deactivated not deleted, and historical events remain available. It also states the ownership enforcement rule. This meaningfully informs the agent of behavioral consequences not fully captured by 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?
The description is two concise sentences, front-loaded with the verb and resource. The second sentence adds essential behavioral details without waste. Every word earns its place, making it highly efficient and readable.
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 one-parameter tool, the description covers the key behavioral aspects: ownership, deactivation, and data retention. It does not describe the return value or error behavior, but no output schema exists and the action is straightforward. The annotations supplement with idempotency and non-destructive hints, so the description is sufficiently complete for the tool's complexity.
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 has 100% coverage with one parameter 'id' and a clear description ('Subscription id (uuid) returned by subscribe'). The tool description merely says 'Cancel a subscription by id' and does not add extra semantic detail beyond the schema. Per the baseline for high schema coverage, a 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') and specifies the resource (subscription), distinguishing it from siblings like subscribe and list_subscriptions. It also adds scope ('Ownership is enforced — you can only cancel your own subscriptions') and clarifies the non-destructive nature, making the purpose unmistakable.
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 this tool: when canceling a subscription, with an explicit ownership constraint. It also implies how it relates to recent_alerts by mentioning historical events stay available, but it does not explicitly name alternatives or state when not to use this tool. This is strong context without exclusions, so a 4 is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Multiple tools are near-duplicates: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded share nearly identical routing, with beta explicitly described as currently identical to stable. The six Polymarket-related tools also form a dense cluster with subtle boundaries, and discover_tools/suggest_questions overlap in onboarding purpose.
Most tools follow a clear snake_case verb_noun pattern (check_password, resolve_entity, compare_entities, list_subscriptions), and family prefixes like ask_pipeworx_* and polymarket_* are applied consistently. Minor deviations exist (ai_visibility_check, pipeworx_trending), but the overall convention is predictable.
32 tools is well past the 25+ threshold and the set feels bloated: several ask_pipeworx variants and Polymarket scanning tools could be consolidated, and unrelated utilities (check_password, scan_dependency, generate_llms_txt) are mixed into what is otherwise a data-research platform. The broad scope does not justify this many top-level entry points.
The main data-research workflow is well covered: routing, grounded verification, deep research, entity resolution/profiles, comparisons, recent changes, discovery, and feedback are all present. Memory and subscription lifecycles are also complete; minor gaps remain such as the lone password tool lacking generation or breach-checking companions, and no direct raw-fetch tool, but these are workable.