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 discloses that the row is deactivated (not deleted) and historical events remain available, adding crucial behavioral context beyond the annotations. 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 that are efficient and front-loaded: the first covers action and constraint, the second explains the behavioral effect. No unnecessary 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?
With one parameter, no output schema, and comprehensive annotations, the description fully covers what the agent needs: ownership enforcement, soft-delete behavior, and parameter usage. No gaps.
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 schema has 100% coverage, and the description adds meaning by stating that the id is a 'Subscription id (uuid) returned by subscribe', which helps the agent understand the parameter's origin.
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 the resource ('subscription'), which distinguishes it 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?
The description specifies ownership enforcement ('you can only cancel your own subscriptions'), providing clear context for when to use the tool. It does not explicitly mention alternatives, but the constraint 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.
The server includes many overlapping tools (e.g., multiple ask_pipeworx variants, epa_regulation vs. epa_search vs. discover_tools). More critically, the tool set covers vastly different domains (Polymarket bets, npm packages, AI visibility, memory storage) alongside EPA regulations, making it hard for an agent to distinguish purposes.
Tool names use a mix of styles: underscore (epa_regulation, ask_pipeworx), camelCase (deep_research, suggest_questions), and verb phrases (scan_competitor_ai_presence). No consistent pattern is followed across the set.
33 tools is high for a server named 'Epa Regulations'. The vast majority are unrelated to EPA regulations (e.g., Polymarket, npm scanning, memory functions), making the scope mismatched. A focused server should have fewer, domain-specific tools.
For a server claiming to be about EPA regulations, only two tools (epa_regulation, epa_search) are directly relevant. The rest are from unrelated domains, leaving severe gaps in expected functionality like rule updates, compliance checks, or cross-referencing with other environmental data.