list_subscriptionsList the caller's active subscriptions. Returns id, type, params, created_at, last_fired_at, fire_count for each. Use this to review what you're monitoring before adding more or to find an id to cancel.
| Name | Required | Description | Default |
|---|---|---|---|
| include_inactive | No | Include cancelled subscriptions in the response (default false). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds return fields beyond annotations, which already declare readOnlyHint=true and destructiveHint=false. No hidden behaviors disclosed, but annotations carry the main burden.
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?
Three sentences, no waste, front-loaded with purpose and return fields, followed by usage guidance.
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 list tool with one parameter and no output schema, the description sufficiently covers return fields and usage context, 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% for the single optional boolean parameter; description does not add semantics beyond schema, maintaining baseline 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 the verb 'List' and resource 'the caller's active subscriptions', lists return fields, and differentiates from sibling tools like subscribe and unsubscribe by mentioning using it to find an id to cancel.
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 says 'Use this to review what you're monitoring before adding more or to find an id to cancel', providing clear context. Lacks explicit exclusion statements but sufficient given sibling tools.
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 have distinct purposes but some overlap exists, e.g., multiple ask_pipeworx variants and deep_research could confuse an agent. Prediction market tools are differentiated but not immediately obvious.
Names are consistently in snake_case but mix verb and noun orders (e.g., 'ai_visibility_check' vs 'ask_pipeworx'). No strict verb_noun pattern throughout.
34 tools is on the high side but still reasonable given the broad domain coverage. Some tools could be consolidated without loss.
Covers data querying, company research, prediction markets, subscriptions, and memory. Minor gaps like no direct web search but ask_pipeworx substitutes.