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namesniper_watch

Start monitoring a taken username so the user can claim it when it frees up or drops (alerts follow the plan's check schedule after two confirming checks). Creates one watch per platform against the plan's slot limit (already-watched pairs are skipped); checks then run automatically on a plan-based schedule and alerts are delivered in-app, by email, and to any configured webhooks. Returns JSON with created watch ids and the skipped count. List watches with namesniper_watches; stop one with namesniper_unwatch. Requires a paid API key (Pro or Business).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
userIdNoIgnored - derived from your API key
usernameYesThe username/handle to watch
platformsNoPlatforms to watch - required; each consumes one watch slot

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / userId / description
      Previous value: -"Ignored — derived from your API key"New value: +"Ignored - derived from your API key"
  2. Changed1 schema field changed
    • changedInput schema / properties / platforms / description
      Previous value: -"Platforms to monitor (default: all supported platforms)"New value: +"Platforms to watch - required; each consumes one watch slot"
  3. First observed

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description fully carries transparency. It discloses slot limits, skip behavior for already-watched pairs, scheduling after two confirming checks, and delivery methods (in-app, email, webhooks). Return format is described briefly. This is thorough for a tool without annotations.

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 well-structured sentences with no waste. Core purpose first, then behavioral details, then return format and sibling references. Every sentence adds value.

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?

Given 3 parameters, no output schema, and no annotations, the description covers purpose, behavior, return, prerequisites, and related tools. It could mention error states like plan limit exceeded, but overall it is sufficiently complete for an agent to use the tool correctly.

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 baseline is 3. The description adds context about watch slots and skipping, but does not significantly augment parameter semantics beyond what the schema already provides (e.g., userId is ignored, platforms consume slots).

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?

The description uses a specific verb ('Start monitoring') and resource ('a taken username') and clearly distinguishes from siblings by naming namesniper_watches and namesniper_unwatch for listing and stopping watches.

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

Usage Guidelines4/5

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

The description states when to use (monitoring a taken username to claim it), mentions prerequisites (paid API key), and references sibling tools for related actions. It does not explicitly state when NOT to use, but the context is clear enough.

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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