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

With no annotations, the description carries the full burden: it does disclose the cost profile ('zero crediti') and that the data is scoped to the most recent checks, which is genuinely useful. It says nothing about permissions, data freshness relative to run_ai_visibility_check, or pagination/volume limits.

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?

A single sentence that front-loads the subject (most-recent AI competitor check) before the parenthetical enumeration of returned metrics. Dense but each clause names a distinct output, so little is wasted; it is slightly run-on.

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?

No output schema exists, so the description must convey the return payload — and it does reasonably well by naming the metrics. However, with zero annotations and no exclusions against similar AI-visibility tools, an agent still lacks enough context to pick this tool confidently over its neighbors.

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?

Only one parameter (project_id), and the schema already documents it at 100% coverage with a pointer to list_projects. The description adds no further parameter semantics, 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?

States a specific resource — competitor AI-visibility data from the most recent checks — and enumerates the concrete outputs (per-engine brand/competitor mention share, deltas, lost prompts, brand and source rankings). The 'AI' framing helps separate it from the generic get_competitors, but it never explicitly contrasts itself with siblings like get_ai_visibility, so differentiation is only implied.

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?

There is no explicit when-to-use guidance and no named alternatives, despite several closely overlapping siblings (get_ai_visibility, get_ai_content_checks, get_competitors). The only usage nudge is the parenthetical 'zero crediti', which hints the call is free but does not tell the agent when this report is the right choice.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.