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add_watch

Start watching a public store collection or category URL (e.g. a Shopify /collections/new-arrivals page) and email the account owner when new products appear. The first scan is a baseline: nothing is emailed. Watch out: the dogfood plan caps watches per account.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "add_watch"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlNoPublic collection or category page URL (https).
emailNoWhen to email about this watch: instant emails right after a scan finds something; daily/weekly hold finds for one roll-up email at the account's chosen slot. Default: instant.
labelNoOptional human name for the watch.
notesNoOptional free-text note.
cadenceNoHow often to re-check the page. Default: daily.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries full behavioral burden and does well: it discloses the non-obvious baseline-scan rule ('nothing is emailed' on first scan) and an account-level limit ('the dogfood plan caps watches per account'). It omits permission/auth requirements and duplicate-watch or error behavior, so it stops short of a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three tight sentences, front-loaded with purpose, then the baseline-scan caveat, then the plan limit. Nothing is redundant and the example URL aids recognition without padding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a five-parameter creation tool with full schema coverage and no output schema, the description covers purpose, key side effect timing, and a quota constraint. It could add what the tool returns (e.g. a watch identifier) or validation failures, but nothing critical for correct invocation is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already documents url, email, label, notes, and cadence including enum semantics and defaults. The description adds no parameter-level detail beyond that, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Start watching a public store collection or category URL') plus the observable effect ('email the account owner when new products appear'), with a concrete example URL type. It does not explicitly differentiate itself from update_watch or get_watch, leaving the add-vs-modify distinction to the names alone.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied by 'Start watching' for a new URL and by the example of a Shopify collections page, and the plan-cap caveat signals a precondition. However, there is no explicit when-to-use vs update_watch guidance and no statement about what happens for an already-watched URL.

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

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