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 this as read-only, idempotent, and non-destructive. The description adds useful context by stating it returns specific fields and that it lists only active subscriptions by default. It also implies the include_inactive parameter affects results, which is beyond the annotation. This is consistent with annotations and adds value.
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, front-loaded with the action, and every sentence serves a purpose. The first sentence states the function and return fields, while the second provides usage context. No filler or redundant information.
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 read-only list tool with one optional parameter, the description covers the purpose, caller scope, return fields, and usage context. Although there is no output schema, the explicit field list compensates. With strong annotations, the description is complete and well-rounded.
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 single parameter (include_inactive) has a comprehensive description in the schema (100% coverage), explaining its meaning and default behavior. The tool description does not add additional parameter context, but the schema is sufficient, so the baseline score of 3 applies.
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 verb ('List') and resource ('the caller's active subscriptions'), providing a specific scope. It distinguishes itself from sibling tools like subscribe/unsubscribe by focusing on listing and reviewing subscriptions. The return fields are explicitly enumerated, making the purpose unambiguous.
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 says when to use the tool: 'Use this to review what you're monitoring before adding more or to find an id to cancel.' This gives clear guidance on when it is appropriate relative to alternative actions (subscribing or unsubscribing), even though it doesn't name the sibling tools directly.
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.
Most tools have distinct purposes, but ask_pipeworx, ask_pipeworx_grounded, deep_research, and validate_claim have overlapping functionality in answering factual questions. The detailed descriptions help differentiate them, though some confusion may still arise.
All tool names follow a consistent snake_case convention with a verb_noun pattern (e.g., compare_entities, resolve_entity). No mixing of camelCase or other styles, making the naming predictable and uniform.
34 tools is on the higher side, but many are meta-tools (discover, feedback, subscriptions) and some are redundant (ask_pipeworx vs grounded). While the scope is broad, the count could be trimmed for tighter focus.
The server covers a wide range of domains (SEC, FDA, FRED, prediction markets, etc.) with strong read and analysis capabilities. Missing update/delete operations and direct trading, but comprehensive for data retrieval and analysis.