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 provide readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds return fields and the effect of the include_inactive parameter, but does not disclose additional behavioral traits beyond what annotations imply.
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, no fluff. The most critical information (lists subscriptions, return fields, usage purpose) is front-loaded.
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 low complexity (single optional parameter, no output schema but described return fields) and rich annotations, the description is fully 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%, and the parameter include_inactive is already well-described in the schema. The description adds no extra semantic value for the parameter.
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 tool lists the caller's active subscriptions with specific return fields (id, type, etc.). It distinguishes well from siblings 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?
Explicit guidance: 'Use this to review what you're monitoring before adding more or to find an id to cancel.' Tells when and why 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.
Many tools overlap in purpose, especially the Pipeworx data retrieval tools (ask_pipeworx, ask_pipeworx_grounded, deep_research) and the Polymarket betting tools (bet_research, polymarket_arbitrage, polymarket_edges, etc.). The Shopify-specific tools are distinct, but the overall set is a confusing mix of domains, making it hard for an agent to select the right tool.
Naming conventions are inconsistent. Some tools use snake_case (ai_visibility_check, bet_research), others use underscores in various patterns (generate_llms_txt, scan_competitor_ai_presence). The Shopify tools use a shopify_ prefix, but the rest follow no uniform scheme, making it unpredictable.
35 tools is far too many for a server named 'Shopify'. Only 5 tools are Shopify-specific; the rest are general-purpose data tools (Pipeworx, Polymarket, memory, etc.). This severe scope mismatch makes the tool count inappropriate and overwhelming for the intended domain.
As a Shopify server, the tools cover only basic read operations (list/get products, orders, customers), missing crucial write operations (create, update, delete) and other Shopify features (webhooks, inventory, etc.). The general tools cover many domains but are not integrated into a coherent Shopify workflow.