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 declare readOnlyHint and destructiveHint false. Description adds default behavior (active only) and optional inactive inclusion, supplementing the safety profile.
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 with no fluff: first states purpose and returns, second gives usage guidance. Front-loaded with the action.
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 and no output schema, the description fully covers purpose, returns, and usage guidance.
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% and description does not add meaning beyond the schema's parameter description. Baseline score is appropriate.
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?
Clearly states it lists active subscriptions and specifies the returned fields. Distinguishes 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?
Provides explicit guidance: use to review before adding more or to find an id to cancel. Implicitly contrasts with adding/subscribing and removing/unsubscribing.
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 clearly distinct purposes, but there is some overlap among ask_pipeworx, ask_pipeworx_grounded, and deep_research, as well as between discover_tools and suggest_questions. However, detailed descriptions help differentiate them.
Naming conventions are highly inconsistent, mixing snake_case (ask_pipeworx, forget), camelCase (discoverTools, suggestQuestions), and underscores (ai_visibility_check, compare_entities). No predictable pattern.
33 tools is on the high side, but the broad domain (finance, pharma, prediction markets, etc.) partly justifies it. However, some tools like forget, remember, recall seem generic and could be separated.
The tool surface covers a wide range of functionalities: visibility checks, pipeworx queries, entity profiles, comparisons, subscriptions, memory, and more. Minor gaps may exist in real-time data or specific niche sources.