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B2B Competitor Monitor — Website Change Tracking (AI)

b2b_competitor_monitor
Read-only

Turn a Maps or LinkedIn company scraper list into an AI 'what changed' website…. Turn a Maps or LinkedIn company scraper list into an AI 'what changed' website feed. Paste a dataset ID. Works with any company scraper output.

Input Schema

NameRequiredDescriptionDefault
inputNoInput for B2B Competitor Monitor — Website Change Tracking (AI). See https://apify.com/noniner/b2b-competitor-monitor.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.4/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds almost nothing behavioral — no mention of how changes are detected, scheduling/cadence, rate limits, or what the resulting feed contains. It does not contradict the annotations.

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

Conciseness2/5

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

The lead sentence is duplicated and visibly truncated mid-word ('website….'), which wastes space and reads as a copy/paste artifact. The remaining two sentences are short but the front-loading is undermined by the broken repetition.

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

Completeness2/5

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

With no output schema, a single opaque nested parameter, and no clarification of what the 'AI what changed' feed returns or how often it runs, the description leaves an agent without enough to invoke the tool confidently. The workflow premise (dataset ID in, change feed out) is the only complete piece of information.

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?

There is a single nested 'input' object parameter with 100% schema description coverage, so the schema carries the documentation burden. The description hints that the input should contain a scraper dataset ID but adds no format, type, or example detail beyond that.

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

Purpose3/5

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

The description conveys the general idea — taking a scraper output list and producing an AI-driven 'what changed' website feed — but the sentence is garbled and duplicated with an ellipsis ('website…. Turn... into'), which obscures whether the output is a feed, a website, or a report. It does not distinguish this tool from nearby siblings like competitor_pulse or signal_radar.

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?

It states one input convention ('Paste a dataset ID') and a compatibility note ('Works with any company scraper output'), but gives no when-to-use guidance, no prerequisites, and no routing to or away from alternatives among the many competitor/signal siblings.

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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