A
license-
qualityA
maintenanceEvaluates any website's AI visibility with 15 checks across crawlability, structure, content, and connectivity, and provides actionable fixes.
Last updated
0
MIT
TofuBofu AI Visibility
by com.tofubofu
Server Details
Free AI visibility scan for any B2B company: see how often AI engines recommend it, plus the fixes.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
A4.7/5.0
Tool DescriptionsA
Average 4.7/5 across 2 of 2 tools scored.
Server CoherenceA
Disambiguation5/5
Each tool has a distinct purpose: one initiates a scan, the other retrieves results. There is no overlap or ambiguity.
Naming Consistency5/5
Both tool names follow a consistent verb_noun pattern in snake_case (scan_ai_visibility, get_visibility_report), making them predictable.
Tool Count5/5
Two tools are exactly right for a simple scan-and-retrieve workflow. Each tool is necessary and sufficient for the server's purpose.
Completeness5/5
The tool surface covers the full lifecycle: starting a background scan and fetching the report. No obvious gaps exist.
Available Tools
2 toolsget_visibility_reportARead-onlyInspect
Fetch the results of an AI-visibility scan started with scan_ai_visibility.
Args:
report_id: The id returned by scan_ai_visibility.
Returns:
While running: {status: "running", progress}. When done: the visibility
score, how often AI mentions the brand, share of voice, top competitors
winning the answers, and the highest-priority fixes, plus the report_url.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| report_id | Yes |
Tool Definition Quality
A4.4/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already set readOnlyHint=true and destructiveHint=false. The description adds behavioral context by describing two possible return states ('while running' vs 'when done'), which clarifies the polling aspect and output structure, going beyond what annotations provide.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is reasonably concise with three sentences: one stating the purpose, and two structured as 'Args' and 'Returns' sections. It is front-loaded and avoids unnecessary words, though could be slightly tighter.
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 tool with one parameter, no output schema, and good annotations, the description covers the purpose, parameter origin, and complete return behavior (including polling states). It fully equips an agent to use the tool 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 description explains the single parameter 'report_id' as 'The id returned by scan_ai_visibility,' adding meaningful context beyond the schema (which has no description and 0% coverage). This informs the agent where the value comes from.
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 'Fetch the results of an AI-visibility scan started with scan_ai_visibility,' which specifies the verb (fetch), resource (results of AI-visibility scan), and explicitly names the sibling tool (scan_ai_visibility) to distinguish itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates that this tool should be used after scan_ai_visibility has provided a report_id, providing clear context for when to use it. It does not explicitly state when not to use it or list alternatives, but the linkage to the sibling tool is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
scan_ai_visibilityAInspect
Start a free AI-visibility scan for a B2B company's website.
Checks how often AI engines (ChatGPT, Claude, Perplexity, Gemini) name the
company when buyers ask for vendor recommendations, and finds the gaps. The
scan runs in the background (roughly 1-2 minutes); call get_visibility_report
with the returned report_id to read the score and findings.
Args:
domain: The company's website or domain, e.g. "acme.com".
email: The user's work email. Required, we send the finished report here
and it identifies the account. One free scan per email per month.
Returns:
report_id, a report_url to view live, and whether an existing report was
reused (free scan already used this month).
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | |||
| domain | Yes |
Tool Definition Quality
A4.9/5.0
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description discloses that the scan runs asynchronously (takes 1-2 minutes), returns a report_id and report_url, may reuse an existing report if the free scan limit is reached, and sends results via email. No contradiction with annotations (readOnlyHint=false, destructiveHint=false).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is well-structured with an introductory sentence, details about the scan's purpose, background process, and parameter explanations. While it is slightly longer, every sentence adds valuable information; could be slightly more streamlined but remains highly effective.
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?
Given no output schema, the description adequately covers return values (report_id, report_url, reuse flag) and the tool's behavior (background scan, email delivery, duration). It provides a complete understanding of what to expect from the tool execution.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, so description bears full burden. It adds meaning to both parameters: domain is described as the company's website (example 'acme.com'), and email is described as user's work email, required for sending report and account identification, with a monthly scan limit.
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 starts a free AI-visibility scan for a B2B company's website, specifies what it checks (AI engine mentions), and distinguishes it from the sibling tool get_visibility_report by mentioning the background process and returned report_id.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use this tool (to start a scan), mentions the sibling tool for reading results, and provides constraints like one free scan per email per month and background execution time (~1-2 minutes). It also includes instructions on what to do after scanning.
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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