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add-connector
Use when adding, modifying, or debugging agent connectors. Provides connector architecture, built-in types, and custom connector template.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Use when adding, modifying, or debugging agent connectors. Provides connector architecture, built-in types, and custom connector template.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Use when instrumenting an application with OpenTelemetry for Agent Health. Provides span structure, required attributes, and config setup for routing traces.
Use when instrumenting an application with OpenTelemetry for Agent Health. Provides span structure, required attributes, and config setup for routing traces.
Add OpenTelemetry instrumentation to an AI agent for Agent Health observability. Use when a user wants to make their agent's traces visible in Agent Health dashboards, or when debugging why traces aren't appearing. Covers span structure, Gen AI semantic conventions, required attributes, and OTLP exporter setup.
Evaluate, benchmark, and improve an AI agent with the Agent Health CLI and server APIs. Use when the user wants to run evaluations/benchmarks, interpret judge results (matcherResults / improvementStrategies), diagnose eval-vs-reality gaps, or raise an agent's pass rate. Mirror of docs/skills/AGENT_HEALTH.md.
Use when the user wants to profile or improve the agent/codebase based on the current session. Profiles this session's traces against a chosen evaluator and proposes concrete edits.
Use when working on config loading, authentication, AWS profiles, or data source resolution. Explains the two config systems (TS vs JSON), auth priority, and multi-profile setup.
| name | add-connector |
| description | Use when adding, modifying, or debugging agent connectors. Provides connector architecture, built-in types, and custom connector template. |
services/connectors/)Pluggable abstraction for agent communication protocols.
types.ts: AgentConnector, ConnectorRequest, ConnectorResponse interfacesregistry.ts: Singleton connectorRegistry — get(), getForAgent()base/BaseConnector.ts: Abstract base with auth header buildingindex.ts: Browser-safe exports (no Node.js deps)server.ts: All connectors including Node.js-only (subprocess, claude-code)| Connector | Protocol | Use Case |
|---|---|---|
agui-streaming | AG-UI SSE | ML-Commons agents (default) |
rest | HTTP POST | Non-streaming REST APIs |
openai-compatible | OpenAI Chat Completions | LiteLLM, Ollama, vLLM |
langgraph | LangGraph REST /invoke | Non-AG-UI LangGraph instances |
strands | Bedrock Agent Runtime | Amazon Strands agents (server-only) |
subprocess | CLI stdin/stdout | Generic command-line tools |
claude-code | Claude CLI | Claude Code agent (extends subprocess) |
kiro | Kiro CLI | Kiro coding agent (extends subprocess; parses [tool] stderr markers) |
pi | Pi CLI | Pi coding agent (extends subprocess) |
mock | In-memory | Demo and testing |
import { connectorRegistry } from '@/services/connectors';
const connector = connectorRegistry.getForAgent(agentConfig);
const response = await connector.execute(endpoint, request, auth, onProgress);
import { BaseConnector } from '@/services/connectors';
class CustomConnector extends BaseConnector {
readonly type = 'custom' as const;
readonly name = 'My Custom Agent';
readonly supportsStreaming = true;
async execute(endpoint, request, auth, onProgress) {
// Your protocol implementation
}
}
connectorRegistry.register(new CustomConnector());
BaseConnector — set
connectorConfig.traceContext so the agent's spans join the eval test_case
trace tree:
propagateEnv: true → inject TRACEPARENT env into subprocess agents (buildTraceparentEnv()).propagateHeader: true → inject a traceparent HTTP header into HTTP/SSE agents (injectTraceparentHeaders()).serviceName: '<otel-service-name>' → service-name + time-window fallback. Defaults: claude-code-agent, kiro-agent, pi-agent, observio-sample-agent. See the "Trace correlation conventions" section in AGENTS.md.SubprocessConnector subclasses) can override
parseStderrChunk(chunk) to turn stderr markers into trajectory steps (how
kiro surfaces [tool] Running: / [tool] status: as action +
tool_result steps). The base class persists stderr to rawOutput and
honors per-request connectorConfig overrides (args / inputMode / timeout).