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, providing the safety profile. The description adds valuable context beyond annotations by specifying that only the caller's subscriptions are listed and that inactive ones are excluded by default unless include_inactive is true. No contradiction with 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?
The description is two sentences: the first front-loads the core action and output, the second gives usage guidance. Every sentence serves a purpose, with no redundancy or fluff.
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 tool's simplicity (one optional parameter, no output schema, complete annotations), the description covers everything needed: what it does, return fields, default behavior, and when to use it. There are no significant 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?
The schema provides 100% coverage for the single parameter include_inactive, including its default value. The description's reference to 'active subscriptions' simply aligns with the schema's 'cancelled subscriptions' but adds no new parameter semantics beyond what the schema already states.
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 uses a specific verb ('List') and resource ('the caller's active subscriptions'), clearly distinguishing this from sibling tools like 'subscribe' and 'unsubscribe'. It also specifies the return fields, leaving no ambiguity about the tool's function.
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?
The description explicitly states when to use it: 'review what you're monitoring before adding more' (i.e., before subscribing) and 'to find an id to cancel' (i.e., before unsubscribing). This gives clear contextual triggers and implies alternatives, making the agent's decision process straightforward.
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.
Each tool has a clearly distinct purpose with detailed descriptions that explain when to use which. Overlapping tools like ask_pipeworx vs ask_pipeworx_grounded are explicitly differentiated by use case (casual vs high-stakes). The Polymarket tools are highly specialized and non-overlapping.
All tool names follow a consistent snake_case pattern with descriptive terms (e.g., ask_pipeworx, resolve_entity, validate_claim). There is no mixing of camelCase or other conventions, making the names predictable and easy to parse.
With 33 tools, the count is above the typical 3-15 range, but it is justified by the server's broad scope covering multiple domains (SEC, FDA, FRED, prediction markets, etc.) and includes meta-tools for discovery and monitoring. Each tool seems necessary for the overall functionality.
The tool surface covers a comprehensive range of operations: data querying, entity profiles, comparisons, monitoring, memory, search, and even feedback. It includes both general-purpose and specialized tools, leaving no obvious gaps for the stated purpose of authoritative data retrieval and analysis.