القائمة
best practices for defining MCP tools using JSON schemas. Use this to design robust `inputSchema`, `outputSchema`, and `annotations` that guide the model effectively.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
| name | mcp-tool-definition |
| description | best practices for defining MCP tools using JSON schemas. Use this to design robust `inputSchema`, `outputSchema`, and `annotations` that guide the model effectively. |
Design "Model-Ready" tools that self-document their purpose, validation logic, and side effects, enabling agents to use them autonomously and correctly.
Every tool must adhere to a strict JSON structure. While inputSchema is required, best practice dictates including outputSchema and annotations for robustness.
{
"name": "create_ticket",
"description": "Creates a new support ticket in the Jira system. Use this when a user reports a bug or feature request.",
"inputSchema": {
"type": "object",
"properties": {
"title": { "type": "string", "description": "Concise summary of the issue" },
"priority": { "type": "string", "enum": ["low", "high"], "description": "Severity level" }
},
"required": ["title", "priority"]
},
"outputSchema": {
"type": "object",
"properties": {
"ticket_id": { "type": "string" },
"status": { "type": "string" }
}
},
"annotations": {
"destructiveHint": true
}
}
framework for implementing "Contract-Adhering Agents." Use this to define precise task specifications, deliverables, and negotiation loops to reduce ambiguity in complex workflows.
implementation patterns for Gemini agents. Use this for coding ReAct loops, defining tools in Python, and using frameworks like LangChain/LangGraph.
methodologies for assessing agent capabilities, tool-use trajectories, and final response quality. Use this to implement automated testing and human-in-the-loop validation for agents.
standardized protocols for agent collaboration. Use this to implement the Agent2Agent (A2A) protocol and Agent Cards to transform isolated agents into a collaborative ecosystem.
strategies for agent observability (logging, tracing, metrics). Use this to instrument agents for debugging, performance tracking, and quality assurance.
operationalization strategies for agents (AgentOps). Use this to manage internal/external tools, optimize agent "brain" prompts, and handle task decomposition.