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). |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, but description adds return fields and optional parameter. No contradictions.
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 waste: first sentence defines purpose and return fields, second provides 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 boolean parameter, description covers purpose, usage, and return fields. Annotations cover safety. No gaps.
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%. Description does not add meaning beyond schema's parameter description, so baseline 3 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?
Description clearly states 'List the caller's active subscriptions' and enumerates return 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?
Explicitly tells when to use: 'review what you're monitoring before adding more or to find an id to cancel', implying 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.
Several tools are near-duplicates or have blurry boundaries: ask_pipeworx and ask_pipeworx_beta are explicitly identical today, and the six polymarket tools (edges, arbitrage, bet_research, fill_risk, edge_tracker, kalshi_spread) all target opportunity-finding in overlapping ways. Detailed descriptions help, but an agent can easily pick the wrong one.
Most names are readable snake_case with clear verbs like ask_, compare_, resolve_, and validate_, but conventions are mixed: noun-style names (entity_profile, recent_alerts, polymarket_edges) sit beside imperative verbs and domain-prefixed families. There is no camelCase or total chaos, so it is inconsistent but navigable.
32 tools is heavy and exceeds the well-scoped zone; the set spans flight search, general data Q&A, prediction markets, memory, subscriptions, and feedback. Many are platform meta-tools that could be consolidated or hidden behind the main ask_pipeworx router.
If Duffel is the intended domain, only duffel_flight_search is present—there is no offer detail, booking, order management, or cancellation, so travel workflows dead-end. As a generic Pipeworx data platform the surface is broader, but that only highlights the mismatch with the server name and a missing coherent domain.