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radveo

how_to_appear_in_ai_search

Get Radveo's honest, practical playbook for getting a local business found and cited inside AI engine answers (ChatGPT, Gemini, Google AI Overviews). Answer-engine optimization (AEO) steps any owner can act on.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYes
noteYesHonesty framing: these steps improve odds, they never guarantee placement.
stepsYesThe AEO steps, in order. Empty only when the server is rate-limiting.
freeCheckUrlYesWhere to run the free AI-visibility check.

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The verb 'Get' implies a read-only, non-destructive operation, which is a positive signal. However, the description does not explicitly state whether the tool has any side effects, requires authentication, or has rate limits. It also does not mention the format of the returned playbook, though an output schema exists. The disclosure is adequate but not comprehensive.

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?

The description is a single, well-structured sentence that fronts the key information: what the tool provides and for whom. It avoids unnecessary detail and is immediately actionable. Every clause contributes to understanding the tool's purpose, making it concise and effectively structured.

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

Completeness5/5

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

For a zero-parameter tool with an output schema, the description is complete. It clearly states what the tool returns (a playbook with AEO steps), the target audience (local business owners), and the scope (AI engine answers). Since an output schema exists, the description does not need to explain return values. The tool is simple and the description covers all necessary context for an agent to invoke it correctly.

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

Parameters4/5

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

The tool has zero parameters, and the input schema is an empty object. The schema description coverage is trivially 100%, and with no parameters to document, the description does not need to add parameter semantics. According to the baseline rule for 0 params, a score of 4 is appropriate; no additional parameter information is needed.

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

Purpose5/5

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

The description clearly states the tool's purpose: 'Get Radveo's honest, practical playbook for getting a local business found and cited inside AI engine answers.' It uses a specific verb ('Get') and a specific resource ('playbook'), and it names the target AI engines. This distinguishes it from the sibling tool 'check_ai_visibility' which presumably checks visibility rather than providing a how-to guide.

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?

The description provides no explicit guidance on when to use this tool versus the sibling 'check_ai_visibility'. It does not mention any alternatives or exclusion criteria. The only implied usage is 'if you want the playbook, use this', but there is no direct comparison or context to help an agent choose between the two tools.

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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TDQS

A3.8/5.0
Disambiguation4/5

The two tools have distinct purposes: one provides a diagnostic score/report, the other offers an instructional playbook. They are clearly separate in function, though both relate to AI visibility. There is minimal risk of one being chosen when the other is intended.

Naming Consistency4/5

Both tool names use lowercase with underscores and are descriptive. 'check_ai_visibility' follows a verb_noun pattern, while 'how_to_appear_in_ai_search' is more of a phrase but still consistent in style and readability. The deviation is minor.

Tool Count3/5

With only two tools, the server feels thin for a domain like answer-engine optimization. While the two tools cover diagnosis and guidance, a more complete server might include additional tools such as generating reports or managing leads. The count is borderline but acceptable for a narrow niche.

Completeness3/5

The server covers two key aspects: assessing readiness and providing actionable steps. However, there are notable gaps—no tool for tracking progress, comparing competitors, or handling specific business categories. The surface is minimal and leaves room for expansion.

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