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 and destructiveHint. Description adds value by specifying return fields and scope ('caller's active subscriptions'), complementing annotations without contradiction.
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 front-loaded with purpose. No redundant words. Efficiently covers purpose, return fields, and usage.
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 low complexity (one optional boolean param, no output schema), the description fully covers purpose, scope, return fields, and usage context. No 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?
Schema coverage is 100% with include_inactive described. Description does not add extra meaning beyond the schema, so baseline score of 3 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?
Clearly states it lists the caller's active subscriptions and specifies the returned fields. Distinguishes 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?
Explicitly mentions when to use: review before adding more or to find an id to cancel. No explicit when-not but 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.
The tool set mixes NASA-specific tools with a large number of financial and prediction market tools, causing confusion. Within the non-NASA tools, there is significant overlap (e.g., multiple Polymarket analysis tools, several research tools with vague boundaries).
Most tools use snake_case, but naming patterns are inconsistent: some start with verbs (search_collections, get_collection), others are noun phrases (entity_profile, deep_research). There is no uniform verb_noun convention across the set.
With 33 tools, the count is high. Although it may be appropriate for the underlying domain (data/prediction markets), it is excessive for the server's stated NASA focus, where only 3 tools are relevant.
For a server named 'Nasa Cmr', the tool set is severely incomplete: only three tools cover NASA Earth science (search/granules/collections), lacking any support for missions, datasets, or advanced queries. The non-NASA tools are comprehensive but disconnected from the server name.