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?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint as true, and destructiveHint as false. The description adds the return fields and default behavior (active only), providing additional useful context beyond 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 concise sentences with no fluff. The first defines the action and output, the second provides usage guidance. Front-loaded with essential information.
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 optional parameter, no output schema, and rich annotations, the description covers purpose, return fields, default behavior, and usage context. It is fully 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%, so the schema already describes the 'include_inactive' parameter and its default. The description implies the default (active subscriptions) but doesn't add new semantic meaning beyond the schema.
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 (list), resource (subscriptions), and scope (caller's active). It distinguishes from sibling tools like subscribe and unsubscribe by focusing on listing existing 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?
Explicitly states when to use: 'to review what you're monitoring before adding more or to find an id to cancel.' Provides clear context for the tool's utility.
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 contains near-duplicate tools (ask_pipeworx_beta explicitly 'currently matches ask_pipeworx exactly') and a dense family of six polymarket_* tools whose boundaries are subtle, plus overlapping onboarding tools in discover_tools and suggest_questions. Detailed descriptions mitigate some confusion, but several tools are difficult to tell apart without reading their full text.
All names are lowercase snake_case and readable, with consistent prefix families (ask_pipeworx, polymarket_, pipeworx_), but the overall structure is mixed: bare verbs (remember, forget, subscribe), adjective+noun names (recent_alerts, recent_changes), and noun+noun domain tags (polymarket_edges, entity_profile) rather than a uniform verb_noun pattern.
At 33 tools the set exceeds the 25-tool threshold and feels heavy, carrying an experimental duplicate of ask_pipeworx and a six-tool polymarket family that could plausibly be consolidated. The breadth reflects several unrelated domains bundled into one server rather than a focused scope.
The data-research core (ask, grounded, deep_research, profiles, comparisons, claim validation, entity resolution) and the prediction-market analysis suite are thoroughly covered, and memory plus subscription lifecycles are complete. However, the events domain the server is named for is thin (only events + metros), and the overall set lacks a single coherent purpose against which completeness can be cleanly judged.