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 key behavioral traits beyond annotations: ownership enforcement, deactivation rather than deletion, and the impact on historical events via recent_alerts. This complements the annotations (e.g., destructiveHint false) and gives the agent a clear picture of side effects.
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 sentences long, front-loaded with the core action, and contains no redundant information. Each sentence adds distinct value (action, ownership, deactivation behavior).
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 tool with annotations and a complete schema, the description fully covers the behavioral context. It explains the ownership rule, the non-destructive nature, and the relationship to recent_alerts, which is sufficient for an agent to use 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?
Although the schema already describes the 'id' parameter with 100% coverage, the description adds meaningful constraints: the id must belong to the caller's own subscription. This provides semantic value beyond the schema's basic type/description.
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 identifies the action ('Cancel a subscription by id') and the resource, and distinguishes itself from sibling tools like subscribe and list_subscriptions. The added detail about ownership enforcement and deactivation clarifies the tool's specific scope.
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 (canceling a subscription) and includes a constraint (ownership). However, it does not explicitly mention alternatives or give when-not-to-use guidance, though the action itself is unambiguous given the tool name and context.
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.
The set mixes several overlapping query surfaces: ask_pipeworx and ask_pipeworx_beta are currently identical, ask_pipeworx_grounded/deep_research/discover_tools/suggest_questions all serve related retrieval/discovery purposes, and the five polymarket_* tools have similar opportunity-finding goals. Only the unusually detailed descriptions save some tools from misselection; an agent would struggle to quickly pick the right one.
Names are uniformly snake_case and mostly follow a verb_noun or prefixed_noun pattern (ask_pipeworx, validate_claim, polymarket_edges, scan_dependency). Minor inconsistencies exist — bare nouns like gene/variant/search sit alongside compound names like generate_llms_txt, and the pipeworx_ prefix isn't applied to ask_pipeworx/deep_research — but the overall style is recognizable and predictable.
36 tools is too many for a coherent server, especially since the domains are largely unrelated: 5 gnomAD genomics tools, 20+ Pipeworx/Polymarket data tools, memory CRUD, subscription management, and a couple of web-dev utilities. The count doesn't align with a single obvious scope and would overwhelm an agent selecting among them.
Within the major subdomains coverage is strong: memory has remember/recall/forget, subscriptions have full lifecycle tools, and Polymarket has edge detection plus fill-risk checking. However, there are notable gaps — no tool to fetch a pipeworx:// citation URI despite deep_research promising resolvable citations, and the gnomAD surface lacks batch queries, coverage, or constraint data for a server named Gnomad.