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 indicate read-only, idempotent, non-destructive behavior. The description adds value by specifying 'active subscriptions' as default and listing return fields, but does not contradict or significantly extend 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: first states purpose, second gives usage and return fields. No fluff, every sentence earns its place.
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 optional parameter and no output schema, the description is fairly complete. It covers purpose, return fields, and usage. Could add pagination details, but it's adequate.
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 parameter is well-documented. The description does not add further semantic meaning to the 'include_inactive' parameter beyond the schema, staying at baseline.
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 'List the caller's active subscriptions', specifying the action, resource, and scope. It also lists the 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 says 'Use this to review what you're monitoring before adding more or to find an id to cancel', providing clear context for when to use this tool over alternatives.
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 distinctly described purposes, but there is some overlap among query tools like ask_pipeworx, ask_pipeworx_grounded, deep_research, and validate_claim, which could cause confusion for an agent.
Tool names are consistently snake_case but vary in pattern: some are verb_noun (ask_pipeworx, compare_entities), while others are noun_noun (entity_profile, polymarket_arbitrage) or longer phrases (scan_competitor_ai_presence), making the naming system inconsistent.
With 33 tools, the server feels over-scoped. Many tools are niche (e.g., polymarket-specific ones) and the high number exceeds the typical range for a focused server, leading to potential overwhelm.
The server covers a broad range of query and monitoring tasks for its domains, but lacks write operations (except memory tools). There are notable gaps like no tool for creating or editing ScienceBase items, which seems incomplete given the server's name.