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 provide readOnlyHint, idempotentHint, and destructiveHint, so the baseline for behavioral safety is covered. The description adds value by stating the exact return fields, particularly last_fired_at and fire_count, which are not obvious from the tool's name. However, it does not detail pagination, ordering, or potential rate limits, which would push it to 5.
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: the first states purpose and output, the second provides usage guidance. Every word is meaningful; no redundancy or filler. The description is front-loaded with the core action and immediately useful information for an AI agent.
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 read-only list tool with one optional parameter and no output schema, the description is substantially complete. It covers purpose, return fields, and usage context. Minor omissions like default limit or ordering could exist but are not critical given the tool's simplicity. The combination with annotations provides a solid understanding.
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 has 100% description coverage for the single parameter include_inactive, so the baseline is 3. The description does not add any additional semantic information beyond what the schema already provides (e.g., it doesn't explain default behavior or implications of the parameter). Hence, a 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?
The description uses the specific verb 'list' and resource 'subscriptions' and clarifies it returns the caller's active subscriptions. It also lists the returned fields, making the tool's purpose crystal clear. The guidance 'to find an id to cancel' implicitly distinguishes from sibling tools like subscribe and unsubscribe, giving it excellent purpose clarity.
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 states when to use the tool: 'to review what you're monitoring before adding more or to find an id to cancel.' This directly ties to sibling tools (subscribe, unsubscribe) and provides clear usage context. No ambiguity about when to employ this tool versus alternatives.
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 has several near-duplicate entries (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded; five polymarket_* tools), and the server name implies topography while most tools serve unrelated data lookups, making it hard to select the right tool for a task.
Most tool names use snake_case and a verb-first style, but there are notable exceptions like 'datasets', 'dem', and 'forget', and the 'pipeworx' prefix is applied inconsistently (pipeworx_feedback, pipeworx_trending vs. ask_pipeworx). The pattern is readable but not fully uniform.
With 34 tools, the count is excessive for a server named Opentopography, especially since only 3 tools (datasets, dem, point_elevation) relate to the implied domain. The bulk of tools belong to a general-purpose data and prediction-market service, creating a severe scope mismatch.
For the implied topography domain, the surface is severely incomplete: only dataset listing, a raster fetch, and a point elevation lookup are present, missing expected operations like elevation profiles, point cloud access, or data processing. For the broader Pipeworx domain, coverage is broad but this does not match the server's stated focus.