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, idempotentHint, destructiveHint. Description adds value by specifying return fields and default behavior (active subscriptions only), which is not in 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 sentences with no fluff. First sentence states purpose and output, second provides usage guidance. Front-loaded and efficient.
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 covers purpose, usage, and return fields adequately. Could mention pagination if applicable but not necessary.
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 optional parameter 'include_inactive'. Description does not mention the parameter, so no added meaning beyond schema.
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 the tool lists the caller's active subscriptions and specifies the returned fields (id, type, params, etc.). It distinguishes from siblings like subscribe/unsubscribe by its listing action.
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'. Provides clear context, though no explicit when-not-to-use or 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 have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-duplicates, and the polymarket_* family has six tools with blurred boundaries. The Vimeo tools are distinct, but the massive unrelated Pipeworx set creates ambiguity about which tool is appropriate for a given task.
Tool names mix conventions: Vimeo tools use bare nouns (video, channel, user), while Pipeworx tools use verb_noun (resolve_entity, validate_claim) or noun_verb (ai_visibility_check). Some names like ask_pipeworx and pipeworx_feedback do not follow a consistent verb-first pattern.
40 tools is far too many for a Vimeo server; only 9 tools are Vimeo-related, and the remaining 31 are an unrelated Pipeworx data toolkit. This inflates the surface area and makes the set unwieldy.
The Vimeo surface covers read operations (search, get, list) but lacks any write operations like upload, update, or delete videos. It also misses common Vimeo features like comments, likes, or portfolio management, so common tasks would hit dead ends.