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 indicate read-only, idempotent, non-destructive. The description adds value by enumerating return fields and clarifying the default behavior (active subscriptions only, with inactive included only via parameter). No 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 sentences, zero filler. The first sentence states the action and return fields; the second sentence gives practical usage context. Every word contributes to understanding.
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 list tool with one optional parameter, full schema coverage, and strong annotations, the description provides all needed information: purpose, scope, return fields, and usage cues. No output schema is needed because return fields are listed.
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 description covers the parameter fully (include_inactive with default false). The tool description does not introduce additional parameter semantics beyond the schema, though it reinforces the default by saying 'active subscriptions'.
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 states a specific action (list) on a specific resource (the caller's active subscriptions) and lists the returned fields. It distinguishes this from sibling tools like subscribe and unsubscribe by focusing on review/listing rather than mutation.
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 gives explicit use cases: 'review what you're monitoring before adding more' and 'find an id to cancel'. It does not name sibling tools subscribe/unsubscribe directly but clearly implies when to use this tool relative to those actions.
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.
Many tools have overlapping purposes (e.g., ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded all route questions; polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker all deal with prediction market edges). The inclusion of memory tools (remember, recall, forget) alongside research tools further blurs boundaries.
Naming conventions are mixed: some tools use snake_case (ai_visibility_check), some use underscores with prefixes (ask_pipeworx, polymarket_arbitrage), and others are more generic (query_layer, layer_info). There is no consistent pattern across the set.
With 34 tools, the set is overly large for a geospatial server; most tools are unrelated to ArcGIS Kansas (e.g., prediction market tools, general research tools). Only 3 tools (search_datasets, layer_info, query_layer) are pertinent, making the count excessive and unfocused.
The server claims to be an ArcGIS Kansas tool but provides only basic layer querying and dataset search. Missing essential GIS operations such as editing, spatial analysis, or advanced queries, making it severely incomplete for its stated purpose.