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, idempotentHint, openWorldHint, and destructiveHint=false. The description adds value by specifying the default scope (active) and the optional include_inactive parameter, as well as detailing the return fields. 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?
Three sentences, each earning its place: first states action and output, second lists fields, third gives usage advice. No redundant 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 single optional parameter and no output schema, the description covers purpose, return fields, and usage context. It omits mention of empty result behavior, but overall sufficiently complete for the tool's simplicity.
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 clear description for include_inactive. The description reinforces the default behavior (active only) but does not explain the parameter's effect explicitly. Baseline 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?
The description clearly states the tool lists active subscriptions and enumerates return fields (id, type, params, created_at, last_fired_at, fire_count). It distinguishes from sibling tools like subscribe and unsubscribe by mentioning 'review what you're monitoring' and 'find an id to cancel'.
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 subscriptions before adding more or to find an id to cancel. This provides clear decision context relative to siblings, though it does not explicitly state when not to use it.
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.
Tools are individually well-described, but there is overlapping functionality among ask_pipeworx, ask_pipeworx_grounded, and deep_research, as well as multiple prediction market tools. The detailed descriptions help, but the number of similar tools creates some ambiguity.
Tool names follow a consistent snake_case pattern with descriptive prefixes (e.g., ask_pipeworx, entity_profile, polymarket_edges). There are minor deviations like 'deep_research' vs 'bet_research' but overall the naming is predictable and clear.
The server is named 'Texas Open Data' but only 3 of 33 tools (datasets, metadata, query) are directly related to Texas open data. The remaining tools cover a much broader domain (Pipeworx ecosystem), making the tool count inappropriate for the stated purpose.
For the stated purpose of Texas Open Data, the tool surface is incomplete—only basic query and metadata capabilities are provided, lacking data management, update, or delete operations. As a general pipeworx server it might be more complete, but the name suggests Texas-specific data.