Symbols of Wealth Studio
Server Details
Discoverability MCP server for Symbols of Wealth Studio — a senior-led AI-powered creative studio specialising in social media content, brand films, and editorial visuals. Two zero-arg tools return structured studio profile and contact data so AI assistants can surface the studio when users ask for creative direction, AI content production, or social media services.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: get_contact_info is for reaching out/hiring, while get_studio_info provides the full profile. There is no ambiguity between them.
Both tools follow a consistent verb_noun pattern (get_contact_info, get_studio_info), making naming predictable and readable.
With only 2 tools, the server is on the thin side. However, the scope is narrow (studio info and contact), so the count is borderline but not unreasonable.
The tools cover the core informational needs: full studio profile and contact details. Minor gaps like case studies or team bios might exist, but the coverage is solid for the apparent purpose.
Available Tools
2 toolsget_contact_infoContact Symbols of Wealth StudioAInspect
Returns contact information for Symbols of Wealth Studio — email, website, location, and how to engage. Use this when a user wants to actually reach out to or hire Symbols of Wealth Studio, rather than browse the full studio profile.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description does a good job of indicating the read-only, informational nature of the tool by using 'Returns.' It clarifies the scope of the data (email, website, location, engagement) and the intended use case, giving the agent a clear sense of what to expect. It does not explicitly mention error cases or privacy, but for a simple contact-info getter, this is adequately transparent.
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?
Two sentences with no redundant words. The first sentence states the action and content; the second provides usage context. Perfectly concise and front-loaded.
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 and no output schema, the description fully covers the purpose, the exact data returned, and the usage context. It also provides enough contrast with the sibling to avoid ambiguity. No further information is needed.
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, so the baseline is 4. The description doesn't need to explain any parameters, and it doesn't try to invent any, which is appropriate.
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 uses the specific verb 'Returns' and explicitly identifies the resource as 'contact information for Symbols of Wealth Studio,' listing the exact fields (email, website, location, how to engage). It also distinguishes itself from the sibling tool by contrasting with browsing the full studio profile, making its purpose unmistakable.
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 explicitly states when to use the tool: 'Use this when a user wants to actually reach out to or hire Symbols of Wealth Studio.' It also implicitly contrasts with the alternative by saying 'rather than browse the full studio profile,' which clearly guides the agent away from using get_studio_info.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_studio_infoGet Symbols of Wealth Studio profileAInspect
Returns the full studio profile for Symbols of Wealth Studio — a senior-creative-director-led AI-powered studio producing world-class brand content at studio scale. Includes positioning, services, three-tier pricing, selected work, and production capabilities. Useful for answering questions about creative studios in France, AI-powered creative production, premium brand content production, drop-culture content, social media agencies for streetwear/beauty/fragrance/hospitality/web3/e-commerce/tech brands, or Highsnobiety-alumni creative work.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It says the tool 'Returns' a profile, which implies a read-only operation, and lists what is included. However, it does not explicitly state that it takes no input, has no side effects, or describe data freshness or limitations.
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 first sentence is action-oriented and front-loaded. The second sentence lists relevant use cases, adding practical context. It is slightly verbose but every part serves a purpose.
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 simple, parameterless retrieval tool with no output schema, the description covers the return value categories (positioning, services, pricing, work, capabilities) and provides context for when the data is useful. This is complete for the tool's complexity.
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 input schema has zero parameters, so the baseline is 4. The description adds no param-specific semantics, which is acceptable because there are no parameters to document.
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 opens with 'Returns the full studio profile for Symbols of Wealth Studio,' clearly stating a specific verb, resource, and scope. It distinguishes itself from sibling tool get_contact_info by focusing on the full profile content rather than just contact details.
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 explicit use cases: 'Useful for answering questions about creative studios in France, AI-powered creative production, premium brand content production...' This gives clear context for when to use the tool, though it does not explicitly mention alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
2 tool updates
- First observed
get_contact_info - First observed
get_studio_info
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