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, openWorldHint, idempotentHint, and destructiveHint. The description adds scope (caller's), default active status, and return field details, providing useful context beyond annotations. It does not mention pagination or rate limits, but the tool's simplicity makes this acceptable.
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 two sentences with no redundant wording. It front-loads the purpose and return fields, then provides usage guidance, making it concise and well-structured.
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 tool with one optional parameter and no output schema, the description covers purpose, return values, and usage context. Combined with the rich annotations, it provides sufficient information for an agent to select and invoke the tool correctly.
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 fully documents the only parameter (include_inactive) with 100% coverage. The description does not add additional parameter-specific details beyond the schema, but its emphasis on 'active' subscriptions hints at the default behavior. Baseline 3 applies due to high schema coverage.
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) and resource (caller's active subscriptions). It also lists the return fields, making the tool's function concrete and distinguishable from siblings 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 provides explicit usage context: 'Use this to review what you're monitoring before adding more or to find an id to cancel.' This clearly indicates when to use the tool, though it does not explicitly name alternative tools.
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.
Several tool clusters overlap heavily: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route natural-language questions to the same underlying catalog, and polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, and polymarket_kalshi_spread all target prediction-market opportunities. entity_profile, recent_changes, and compare_entities also share company-research territory, making misselection likely without reading long descriptions carefully.
All names use snake_case, but conventions are mixed: some are verb_noun (list_subscriptions, generate_llms_txt, resolve_entity), some are noun phrases (entity_profile, rba_cash_rate), and some are brand-prefixed product names (ask_pipeworx, pipeworx_trending). The polymarket_* and rba_* families are internally consistent, but the overall surface has no single predictable pattern.
35 tools is a large surface, well above the 25+ threshold that typically becomes unwieldy. While the server covers a broad domain (data lookup, prediction markets, memory, subscriptions, company research), many tools are niche variants (ask_pipeworx_beta, polymarket_edge_tracker, scan_competitor_ai_presence) that add cognitive load rather than earning their place.
Core flows are well covered: memory has remember/recall/forget, subscriptions have subscribe/list/unsubscribe/recent_alerts, and data access has ask_pipeworx plus grounded and research variants. However, the surface is sprawly and uneven — prediction markets get six tools while other domain areas rely on generic routing, and the server's overall purpose is diffuse enough that gaps are hard to assess cleanly.