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serp_ai_monitor

Read-only

SERP + AI answer check for up to 10 keywords on 1 AI engine. Price: $0.70 USDC per call on Base, paid with x402; not charged if the call fails.

Input Schema

NameRequiredDescriptionDefault
brandNoBrand name to look for in AI answers
domainYesYour site, e.g. notion.com
countryNoTwo-letter country code, e.g. us
keywordsYesKeywords to check, capped by the tier
languageNoTwo-letter language code, e.g. en
previousSnapshotNoA previous response, to get rank changes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, and the description adds genuinely new behavioral facts: cost of $0.70 USDC per call, payment via x402 on Base, and no charge on failure. These are exactly the cost/auth details an agent needs before incurring a paid call; only the response shape is left unstated.

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?

Two short sentences with zero waste: the capability and its limits come first, pricing and failure-billing second. Nothing is repeated from the schema or annotations.

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

Completeness3/5

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

Safety and cost are fully covered, but with no output schema the description gives no hint of what a response contains (SERP results, AI answer mentions, rank deltas via previousSnapshot). For a monitoring/comparison tool with a previousSnapshot input, that gap matters.

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 description coverage is 100%, so every parameter is already documented, establishing a baseline of 3. The description adds only the tier semantics ('up to 10 keywords') that clarify what 'capped by the tier' means for the keywords array, but says nothing about country/language/previousSnapshot usage.

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 concrete verb+resource: 'SERP + AI answer check' for keywords against an AI engine, with an explicit tier limit (10 keywords, 1 engine). This implicitly distinguishes it from serp_ai_monitor_deep and the ai_visibility family, but it never names or routes to those siblings explicitly.

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

Usage Guidelines2/5

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

No explicit statement of when to use this versus serp_ai_monitor_deep (presumably a deeper tier) or ai_visibility/ai_visibility_quick. The only selection signal is the implicit 'up to 10 keywords on 1 engine' cap, leaving the agent to infer the trade-off.

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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