alerts_pendingCheck which watched items got cheaper: lists each watch at or below its target, or dropped 5% or more since the last observation, with change % and confidence.
Answer "did anything I watch get cheaper?": lists every watch whose latest price is at or below its target, or which dropped 5% or more against the previous observation, with the change % and the reading confidence.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.20.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavior. It is transparent about what the tool returns: watches meeting the stated price-drop criteria, along with change percentage and reading confidence. It does not mention data freshness or whether it triggers refreshes, but for a list-like read operation this is reasonably complete.
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?
A single sentence packs the purpose, the triggering question, the two inclusion criteria, and the key output fields without any filler. It is front-loaded with the user intent and stays tightly scoped.
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 zero-parameter tool, the description is sufficient to call it and understand the return value's key fields. It leaves minor ambiguity around terms like 'target' and 'previous observation', but the overall behavior is clear and no output schema exists to compensate.
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 tool has zero parameters, so the input schema is empty and 100% covered. The description does not need to document parameter semantics. Baseline 4 applies because there is nothing missing for an invocation.
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 ('lists every watch') and defines the exact conditions for inclusion (price at/below target, or ≥5% drop). It clearly differentiates itself from siblings like watch_list (all watches) and price_check (single current price) by focusing on pending discount alerts.
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 opening phrase 'Answer "did anything I watch get cheaper?"' gives a clear trigger for when to use this tool. It does not explicitly exclude alternatives such as price_check or watch_list, but the use case is implied well enough for an agent to select it correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.