get_latest_scoreGet the AI Visibility Index (0-100) for the signed-in user's most recently scanned brand, broken down by engine. Requires a free Ninar account (no credit card).
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is known. The description adds useful context: it requires a free Ninar account and explains the scope (most recent brand). It does not fully describe error cases, but with annotation coverage, this is sufficient.
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?
The description is two sentences long, front-loaded with the primary purpose, and every clause adds value. The first sentence states what and for whom, and the second states the account requirement. No filler or repetition.
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?
For a tool with no parameters, no output schema, and simple semantics, the description covers the essential elements: the metric, its range, the scope, and a prerequisite. It could be more explicit about the response format (e.g., structured by engine), but it's adequate for a simple read operation.
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?
The tool has zero parameters, and the schema is empty. The description clarifies the implicit inputs (signed-in user and most recently scanned brand), which adds meaning beyond the empty schema. This meets the baseline 4 and exceeds it by specifying implicit context.
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 description clearly states a specific verb ('Get') and resource ('AI Visibility Index'), defines the numeric range (0-100), and specifies the scope ('signed-in user's most recently scanned brand') and breakdown ('by engine'). This distinguishes it from sibling tools like scan_visibility and audit_brand_visibility, which have different purposes.
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?
The description provides clear context for when to use the tool: it retrieves the latest score for the user's most recent scan, and it notes the account prerequisite. However, it does not explicitly contrast with alternatives or state when not to use it, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a unique aspect of brand visibility management: scanning, auditing, listing gaps, generating content, and retrieving scores. No two tools overlap in function.
All tool names follow a consistent verb_noun pattern using snake_case (e.g., scan_visibility, get_latest_score). This makes it easy for an agent to infer action and target.
With 5 tools, the server covers the core workflows of scanning, auditing, content gap analysis, content generation, and score retrieval without being bloated or sparse.
The tool surface provides a complete lifecycle for brand visibility analysis: scan → audit → identify gaps → generate content → get score. No obvious missing operations.