Tool Description Semantic Density Scorer Connector for AI agents.
3 live capabilities
Optimize function calling precision and parameter consistency
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Why people use Tool Description Semantic Density Scorer
Capability Description Semantic Density Scorer solves messy function calling
This MCP automates that audit. You get an instant score on how readable and actionable your definitions are.
What Vinkius changes
You stop guessing if your instructions are clear enough for an agent to follow.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 5,900+ Connectors
- Real-world use case 01
Scaling a large toolset
You are adding 50 new capabilities and need to ensure they all follow the same naming rules without manual checking.
- Real-world use case 02
Debugging function failures
An agent keeps failing to call a specific function, so you check if the description is too vague or lacks verbs.
- Real-world use case 03
Refining prompt efficiency
You want to make your capability definitions as dense and efficient as possible to save tokens during long conversations.
Complete set · 3capabilities
The complete Tool Description Semantic Density Scorer capability set.
These are the exact actions your AI can choose when you ask it to work with Tool Description Semantic Density Scorer.
01—03
3 capabilities in this set.
Part of 3 available through Tool Description Semantic Density Scorer.
- 01 Capability
Analyze naming uniformity
Checks if your parameters follow a consistent casing style like snake_case or camelCase. It prevents parsing errors in your client.
- 02 Capability
Calculate verb density
Measures how many action-oriented verbs are in your text to help remove unnecessary fluff. This helps reduce token waste.
- 03 Capability
Evaluate description clarity
Combines density and naming checks to give you a final score on how well an agent will understand the capability.
Set up in minutes
One URL. Then ask Tool Description Semantic Density Scorer to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Tool Description Semantic Density Scorer from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_ZgfgQL81tK2KxCGQ3HRK0AigWOuqKt5KVLonvnoZ/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it Tool Description Semantic Density Scorer, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Tool Description Semantic Density Scorer for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_ZgfgQL81tK2KxCGQ3HRK0AigWOuqKt5KVLonvnoZ/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the Tool Description Semantic Density Scorer URL.
- Step 03
Save and start
Save the connection and enable Tool Description Semantic Density Scorer in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"tool-description-semantic-density-scorer": {
"url": "https://edge.vinkius.com/vk_preview_ZgfgQL81tK2KxCGQ3HRK0AigWOuqKt5KVLonvnoZ/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using Tool Description Semantic Density Scorer
Open Agent mode in chat and ask: "Using Tool Description Semantic Density Scorer, help me...". 3 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"tool-description-semantic-density-scorer": {
"url": "https://edge.vinkius.com/vk_preview_ZgfgQL81tK2KxCGQ3HRK0AigWOuqKt5KVLonvnoZ/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using Tool Description Semantic Density Scorer
Ask Copilot: "Using Tool Description Semantic Density Scorer, help me...". 3 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"tool-description-semantic-density-scorer": {
"url": "https://edge.vinkius.com/vk_preview_ZgfgQL81tK2KxCGQ3HRK0AigWOuqKt5KVLonvnoZ/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using Tool Description Semantic Density Scorer
Open Cascade and ask: "Using Tool Description Semantic Density Scorer, help me...". 3 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"tool-description-semantic-density-scorer": {
"url": "https://edge.vinkius.com/vk_preview_ZgfgQL81tK2KxCGQ3HRK0AigWOuqKt5KVLonvnoZ/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using Tool Description Semantic Density Scorer
Ask Cline: "Using Tool Description Semantic Density Scorer, help me...". 3 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add tool-description-semantic-density-scorer --transport http "https://edge.vinkius.com/vk_preview_ZgfgQL81tK2KxCGQ3HRK0AigWOuqKt5KVLonvnoZ/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using Tool Description Semantic Density Scorer
Ask Claude: "Using Tool Description Semantic Density Scorer, show me...". 3 tools are ready
Where the request belongs
Work Tool Description Semantic Density Scorer can move forward.
This is for the engineers building reliable toolsets who can't afford runtime errors caused by vague text or inconsistent parameter naming.
LLM Engineer
Auditing function definitions for production reliability and token efficiency.
Prompt Engineer
Refining capability instructions to ensure they are highly actionable and precise.
Agent Developer
Ensuring parameter consistency across a large library of custom capabilities.
Build the capability set
Add more capabilities.
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Bring your own AI
Change the model, client or framework. Keep Tool Description Semantic Density Scorer connected.
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Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
JetBrains -
Warp -
Amazon Q -
Antigravity -
BoltAI -
Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about Tool Description Semantic Density Scorer.
The practical details behind the request, access and result.
How does Capability Description Semantic Density Scorer help with function calling?
It audits your capability definitions to ensure they are precise and structurally sound. This prevents errors during the execution phase.
Can I use Capability Description Semantic Density Scorer to find errors in my parameters?
Yes, it specifically checks for naming inconsistencies like mixed casing styles that can break your integration.
Does Capability Description Semantic Density Scorer work with Cursor or VS Code?
It works with any MCP-compatible client, including Cursor, VS Code, and Claude Desktop.
Will Capability Description Semantic Density Scorer help me save tokens?
Yes, by identifying unnecessary fluff in your descriptions, you can rewrite them to be more dense and efficient.
Is Capability Description Semantic Density Scorer useful for prompt engineering?
Absolutely. It provides a way to measure the linguistic precision of your instructions, which is core to effective prompt engineering.
What is semantic density in the context of capability descriptions?
Semantic density refers to the ratio of actionable information to total text length. A high-density description uses imperative verbs and provides clear return types, minimizing linguistic noise that can distract an LLM during function calling.
How does the `analyze_naming_uniformity` capability work?
The analyze_naming_uniformity capability inspects an array of parameter names to detect deviations from a primary casing convention, such as camelCase or snake_case. It returns a uniformity score and identifies the detected style.
Can this server help improve my agent's reliability?
Yes. By using evaluate_description_clarity, you can identify descriptions that lack explicit return types or use ambiguous language, allowing you to refine your capabilities for more deterministic and reliable execution in AI clients.
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