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 mark readOnlyHint, idempotentHint, etc. Description adds that it returns specific fields and mentions the 'include_inactive' parameter, providing extra context beyond 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 concise sentences with no wasted words. Front-loaded with the core 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?
With no output schema, description adequately lists return fields. Parameter covered. Sibling context provided. Complete for a simple read-only list tool.
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% (single parameter fully described). Description does not add new meaning beyond the schema, earning baseline 3.
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 (id, type, params, etc.). Distinguishes from sibling tools like subscribe/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 guides when to use: 'review what you're monitoring before adding more or to find an id to cancel'. No when-not stated, but context is clear.
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.
Tools cover a wide range of domains (TV, finance, betting, memory, etc.), each with detailed descriptions that help distinguish their purposes. However, some overlap exists between related tools like bet_research, polymarket_arbitrage, and polymarket_edges, though the descriptions clarify their distinct uses.
Most tool names follow a consistent verb_noun pattern with underscores (e.g., get_show, list_episodes, resolve_entity). A few tools use single imperative verbs (remember, recall, forget), which is a minor deviation but still clear.
The server has 31 tools, which is on the higher side. While each tool has a defined purpose, the scope seems too broad for a server named 'Tvmaze', as many tools are unrelated to TV (e.g., company analysis, betting, memory). A more focused set would improve coherence.
For a general-purpose data server, the tool set covers a wide range of tasks: TV show lookups, company research, betting analysis, memory management, and more. The inclusion of ask_pipeworx as a fallback for many queries compensates for missing specific tools. However, the TV-specific functionality is limited to search and schedule, missing details like cast or crew.