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 and destructiveHint=false. Description adds that it returns active subscriptions (default) and lists specific fields, complementing annotations without contradicting them.
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. Purpose and usage are front-loaded, and every sentence adds value.
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 fully covers purpose, return fields, usage context, and parameter implication.
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% for the single parameter 'include_inactive'. Description implies default behavior (active only), adding minimal value beyond the schema's definition.
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 uses specific verb 'List' and resource 'subscriptions', clearly distinguishing from sibling tools like subscribe/unsubscribe. It also enumerates returned fields (id, type, params, etc.).
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?
States 'Use this to review what you're monitoring before adding more or to find an id to cancel', providing clear when-to-use guidance. Not explicitly mentioning alternatives, but context suggests siblings handle mutations.
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.
The five WooCommerce tools are clearly distinct, but the remaining 31 Pipeworx tools contain several overlapping query/research entry points (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, validate_claim) that an agent would struggle to tell apart without deep inspection. The context of the server also misleads: an agent expecting WooCommerce tools must navigate a much larger unrelated research toolkit.
The woo_* tools follow a clean verb_noun pattern, but the bulk of the set uses wildly mixed conventions: bare verbs (forget, recall, subscribe), noun phrases (entity_profile, recent_changes), generic names (ask_pipeworx, discover_tools), and vendor-prefixed variants (pipeworx_trending, polymarket_edges). There is no single naming system across the server.
36 tools is far too many for a server whose apparent purpose is WooCommerce store access; only 5 tools actually relate to WooCommerce. The remaining 31 are an unrelated general-purpose data research suite, making the toolkit feel bloated and mis-scoped.
The WooCommerce surface is severely incomplete: it only supports read operations (get/list for products, orders, customers). There are no create, update, delete, refund, or other write operations, so an agent cannot actually manage a store. The unrelated Pipeworx tools do not fill these gaps.