tickerbot_subscribe_events

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden and does an exceptional job. It discloses the delivery payload structure ('events.fired' with an events array), latency expectations (analyst ≤1h, corporate daily), the need for paid plans (webhook slots), and the composable filter semantics. This is rich, non-obvious behavioral context that goes well beyond what the name or schema alone would convey.

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 dense but every sentence earns its place: it states the core purpose, explains the two filters with concrete examples, notes the paid plan requirement, describes the delivery payload, and gives a latency caveat. There is no fluff or repetition; it is structured to front-load the most important information (what and when) before finer details.

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 create-operation tool with 10 parameters and no output schema, the description covers most essential context: purpose, event types, filter usage, delivery format, latency, and pricing. The only notable gap is that it does not describe what the tool returns upon success (e.g., a webhook ID or confirmation), which would be helpful given the lack of an output schema.

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 already describes all 10 parameters (100% coverage), so the baseline is 3. The description adds meaning by explaining the conceptual distinction between q (ticker state) and event_q (event content), and why kinds is a comma-list string rather than an enum (to allow multi-kind values). This clarifies design rationale and helps the agent form correct queries, raising the score above baseline.

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 opens with 'Create an event-trigger webhook: fires when NEW events land', which clearly states the specific verb (create), resource (event-trigger webhook), and behavior (fires on new events). It enumerates event kinds (dividends, splits, insider filings, analyst actions) and includes examples, making it unmistakable what the tool does and how it differs from generic webhook creation tools like tickerbot_create_webhook.

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 clear context for when to use this tool (event-driven notifications for specific corporate events) and hints at an exclusion by contrasting latency: 'NOT sub-minute like state webhooks'. However, it does not explicitly name sibling alternatives (e.g., tickerbot_subscribe_ticker) or state when not to use it, so it stops short of a fully explicit when/when-not guide.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.