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

With no annotations, the description carries the full behavioral burden and does so: it discloses the required Apify auth scheme (Authorization: Bearer), rate limits (60 calls/min/IP), the 100-item cap with no pagination, and the pricing model ($1.00 per run + $0.50 per business audited). It also explains that the website is scanned 'without a browser', which tells the agent the scan is passive. This is unusually rich disclosure for a no-annotation tool.

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

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

It is front-loaded: purpose first, then the trigger, then sibling routing, then operational constraints. The first sentence is very dense with a long deliverables list, and the auth/rate/pricing tail is compact but adds bulk. Efficient overall, though the opening could be trimmed slightly.

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

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

There is no output schema and no annotations, so the description must cover purpose, routing, outputs and operations — and it does all four, even enumerating the concrete deliverables (llms.txt, LocalBusiness JSON-LD, AI-drafted review responses, action plan). An agent has everything needed to decide and invoke correctly.

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

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

Schema description coverage is 100%, so the schema already documents all six parameters (query, dryRun, language, maxReviews, websiteUrl, proxyConfiguration) in detail. The description adds no parameter-level syntax or semantics beyond what the schema provides, so the baseline 3 applies.

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

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

The opening sentence names a specific verb+resource ('Deep audit of ONE local business's online presence in a single run') and enumerates exactly what the audit covers: Google Business Profile data, reviews, website AI-readiness, a /100 score, and deliverables. It is immediately distinguishable from every sibling because it explicitly contrasts itself with google_maps_scraper, aeo_ai_visibility_checker and review_radar.

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

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

It states the positive trigger ('before selling it marketing services', checking whether ChatGPT/Perplexity/Gemini can see it) and then names three alternatives with the exact condition that selects each: raw LIST of many businesses → google_maps_scraper; website-only technical check → aeo_ai_visibility_checker; ongoing monitoring of NEW reviews → review_radar. 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.