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 provide readOnlyHint, idempotentHint, etc. Description adds value by listing return fields and usage context, with no contradiction.
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 front-loading the primary purpose and usage, with no unnecessary content.
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?
Given the tool simplicity (one optional param, no output schema), description fully covers purpose, output, and usage context.
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 description doesn't need to elaborate; it repeats parameter name but adds no new semantics beyond 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?
Description clearly states 'List the caller's active subscriptions' with specific verb and return fields, distinguishing it from sibling tools like subscribe and unsubscribe.
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 advises using this to review monitoring before adding more or to find an id to cancel, providing context for when to use it.
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.
Most tools have distinct purposes, but pairs like ask_pipeworx/ask_pipeworx_grounded and bet_research/polymarket_edges could cause confusion without careful reading. Overall, descriptions are clear enough to differentiate.
Names are snake_case and mostly follow verb_noun pattern, but several are noun_noun (entity_profile, pipeworx_feedback, polymarket_arbitrage) creating inconsistency. Still readable due to descriptive terms.
33 tools is slightly high but justified given the broad scope (data retrieval, prediction markets, memory, subscriptions). Each tool serves a specific role, so the count feels appropriate for the platform's capabilities.
The tool set covers data retrieval, prediction market analysis, memory management, and subscriptions well. Minor gaps exist (e.g., no direct betting tool), but core workflows are supported comprehensively.