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 and idempotentHint. Description adds that it returns specific fields and lists only active subscriptions by default, with an option to include inactive. No contradictions.
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, succinct, front-loaded with the core purpose. No unnecessary words.
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 simple tool (one optional param, good annotations, no output schema needed), the description fully covers what an agent needs: purpose, output, default behavior, and usage hints.
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?
Input schema has 100% coverage for the single parameter 'include_inactive' with its own description. The description reiterates the default behavior but adds no new parameter semantics beyond what the schema provides.
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?
Clearly states the action ('List the caller's active subscriptions') and specifies return fields. Differentiates from sibling tools like subscribe and unsubscribe by focusing on listing existing subscriptions.
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 says when to use: 'to review what you're monitoring before adding more or to find an id to cancel'. Provides concrete use cases.
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 there is some overlap between ask_pipeworx, ask_pipeworx_grounded, deep_research, and similar data query tools. However, detailed descriptions help agents differentiate.
Names consistently use snake_case and a mix of verb_noun and noun_verb patterns. No camelCase is present, but some tools like 'generate_llms_txt' have embedded acronyms, which slightly reduces consistency.
33 tools is high, but the server covers a wide range of functionalities (data lookups, prediction markets, RSS feeds, memory). Some tools could be combined, but the count is within reasonable limits for a comprehensive tool server.
The tool set covers major areas like entity lookups, prediction market analysis, data retrieval, and memory management. Minor gaps exist (e.g., no RSS feed deletion tool), but overall it is quite comprehensive.