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). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds value by specifying the return schema (id, type, params, created_at, last_fired_at, fire_count) and the default filtering to active subscriptions, which is beyond the 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 concise at three sentences, with no redundancy. It front-loads the core purpose and efficiently delivers usage guidance and return structure.
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), the description covers the essential aspects: what it does, what it returns, and when to use it. It could mention that results are paginated or sorted, but this is not critical for a basic list operation.
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%, with a well-described boolean parameter 'include_inactive.' The description does not add new semantic meaning to the parameter beyond what the schema provides, so baseline score is appropriate.
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 begins with 'List the caller's active subscriptions,' clearly stating the action (list) and resource (subscriptions), including scope (caller's active). The return fields are enumerated, and the tool is distinct from sibling tools like subscribe and 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?
The description explicitly advises using this tool to 'review what you're monitoring before adding more or to find an id to cancel,' providing clear when-to-use guidance. It does not explicitly mention when not to use it, but the context is sufficient.
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 some overlapping function sets (e.g., multiple Polymarket tools, multiple ask/research tools) could cause confusion. However, descriptions are detailed enough to differentiate.
Naming is mostly consistent with snake_case and verb+noun patterns, but a few tools start with nouns (polymarket_*, pipeworx_*), creating minor inconsistency.
At 32 tools, the server feels heavy and covers many disparate domains. While each tool has its place, the high count strains coherence.
Given the server name 'Rentcast', only two tools relate to rental data. The rest cover unrelated domains, leaving a major gap for the intended primary purpose.