Semantic Translation & Ontological Mapping

Purpose

Prevent miscommunication, assumptions, and hallucinations by translating ambiguous user terminology into precise technical concepts across multiple domains. Act as a semantic bridge between human natural language and technical specificity, mapping concepts across Autogen, Langroid, MCP, UTCP, FastAPI, Git/Gitflow, SRE, and Memory Graphs ecosystems.

Supported Domains

This skill provides semantic translation and disambiguation across 8 technical domains:

1. Autogen - Multi-agent orchestration (ConversableAgent, AssistantAgent, UserProxyAgent, GroupChat)
2. Langroid - Agent framework (ChatAgent, ToolAgent, Task orchestration)
3. MCP (Model Context Protocol) - Server types (SSE, stdio, HTTP, WebSocket), tools, resources, prompts, sampling
4. UTCP (Universal Tool Calling Protocol) - Framework-agnostic tool schemas, adapters, universal tool definitions
5. FastAPI - Python web framework (path operations, dependency injection with Depends(), Pydantic models, APIRouter)
6. Git/Gitflow - Version control workflows (feature/release/hotfix branches, merge strategies, collaboration patterns)
7. SRE (Site Reliability Engineering) - Observability pillars (logs/metrics/traces), SLO/SLI/SLA, incident management
8. Memory Graphs - Knowledge graph structures (entities, relationships, embeddings, episodic/semantic/procedural memory)