unsubscribeCancel a subscription by id. Ownership is enforced — you can only cancel your own subscriptions. The row is deactivated (not deleted) so its historical events stay available via recent_alerts.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Subscription id (uuid) returned by subscribe. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes beyond annotations: 'The row is deactivated (not deleted) so its historical events stay available via recent_alerts.' Annotations already indicate mutation (readOnlyHint=false) and idempotency, but description adds critical soft-delete behavior.
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 wasted words. Main action first, then additional details in a natural flow.
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 tool with 1 param, no output schema, no nested objects, the description fully covers input, behavior, side effect, ownership constraint, and post-effect (data still available via recent_alerts).
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?
For the single 'id' parameter, the description adds 'Subscription id (uuid) returned by subscribe' which tells where to get the value. Schema already describes it as a uuid, so description adds provenance context.
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 'Cancel a subscription by id' (specific verb+resource), and distinguishes from sibling tools like 'subscribe' and 'list_subscriptions' by mentioning ownership enforcement and the deactivation effect.
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 says when to use (with a subscription id) and the ownership constraint. Lacks explicit when-not-to-use or alternatives, but the sibling list provides context.
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 tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and discover_tools all serve general data querying, while bet_research, polymarket_edges, polymarket_arbitrage, and polymarket_edge_tracker all target prediction-market opportunities. An agent would struggle to pick the right one consistently despite long descriptions.
Naming conventions are mixed: some tools use snake_case bare verbs (remember, recall, forget), some use a pipeworx_ prefix, some use tradier_ prefix, and some use descriptive phrases (generate_llms_txt, scan_competitor_ai_presence). There is no consistent verb_noun or prefix pattern across the set.
34 tools is on the heavy side, but more importantly the count does not match the server's stated identity. The server is named Tradier, yet only 3 of 34 tools are Tradier-specific market data tools; the rest are Pipeworx research, prediction-market, memory, and subscription utilities. The scope feels bloated and unfocused.
For a server named Tradier, the surface is severely incomplete: only quote, option expirations, and option chain are provided. Missing are account info, positions, orders, historical data, watchlists, and other core brokerage/trading operations. The Pipeworx research side is broad, but the apparent trading domain has major gaps that would cause agent failures.