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Web Monitor List

web_monitor_list
Read-onlyIdempotent

List the scheduled change monitors owned by the calling IP, with latest/next check time, last title or error, and the 5 most recent change events. When to use: after web_monitor_set, poll this instead of re-fetching the page; or to show the user what is currently being watched. Do not use: to create a monitor (web_monitor_set) or to compare one page now (web_diff). Returns: {ok, count, monitors:[{monitor_id,url,interval_minutes,active,created_ts,last_check_ts,next_check_ts,last_title,last_error,webhook_enabled,events_total,recent_events}], note}. Pass monitor_id to get that one monitor plus last_event.diff (the most recent detected change, up to 4000 chars) so you can read what changed without a webhook. Free (not metered); rate-limited to 20 calls/min per IP.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
monitor_idNoOptional: return this monitor (owned by the calling IP) plus its most recent change diff.
include_diffNoWith monitor_id, include the latest unified diff. Default true.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already cover read-only/idempotent/non-destructive, and the description adds the traits annotations can't: ownership is scoped to the calling IP, the call is free but rate-limited to 20 calls/min, and passing monitor_id unlocks the last diff. The full return object shape is spelled out. This is genuinely additive behavioral context.

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

Conciseness4/5

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

Front-loaded with purpose, then usage, then returns, then cost — a sensible ordering. The inline return-shape enumeration is dense and slightly heavy, but every element conveys something an agent needs.

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

Completeness5/5

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

There is no output schema, so the description compensates by enumerating the returned object including nested monitor fields and the events array. With rate limits, ownership scope, and the monitor_id variant all covered, an agent has everything needed to call it correctly.

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

Parameters4/5

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

Schema coverage is 100%, so both parameters are already documented; baseline would be 3. The description still adds value by tying monitor_id to the concrete outcome (single monitor plus last_event.diff, up to 4000 chars), which the schema does not state.

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

Purpose5/5

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

States a specific verb and resource ('List the scheduled change monitors') with an explicit scope ('owned by the calling IP') and enumerates the returned fields. It also names the siblings it is not (web_monitor_set, web_diff), so an agent can distinguish it without opening a schema.

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

Usage Guidelines5/5

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

Explicit when-to-use ('after web_monitor_set, poll this instead of re-fetching') and an explicit 'Do not use' clause naming the correct alternatives for creation and one-off comparison. Nothing is left to inference.

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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