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Use when integrating LLM calls via LiteLLM/Bedrock for evaluation or content generation
Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.
Basierend auf der SOC-Berufsklassifikation
Record browser-based feature demos as GIFs via Playwright and optionally document them in docs/features/index.md. Trigger with "Demo <feature>" or "Demo and Document <feature>".
Use when creating service modules in apps/api/skillhub/services/
Use when writing API tests in apps/api/tests/
Use when implementing division-based access control on any endpoint
Use when adding services to docker-compose.yml or creating Dockerfiles
Use when implementing error handling across the API, frontend, or MCP server
| name | llm-integration-builder |
| description | Use when integrating LLM calls via LiteLLM/Bedrock for evaluation or content generation |
import httpx
async def call_llm(prompt: str, content: str) -> dict:
if not settings.LLM_ROUTER_URL:
return {"pass": True, "score": 85, "findings": [], "skipped": True}
response = await httpx.AsyncClient().post(
f"{settings.LLM_ROUTER_URL}/v1/chat/completions",
json={
"model": "bedrock/anthropic.claude-3-5-sonnet-20241022-v2:0",
"messages": [
{"role": "system", "content": prompt},
{"role": "user", "content": content}
]
},
timeout=30.0
)
return parse_verdict(response.json())
flag = db.query(FeatureFlag).filter_by(key="llm_judge_enabled").first()
if not flag or not flag.enabled:
return JudgeVerdict(passed=True, score=85, findings=[], skipped=True)
{"pass": true, "score": 82, "findings": [
{"severity": "medium", "category": "quality", "message": "..."}
], "summary": "..."}
Score >= 70 = pass. Any CRITICAL finding = auto-fail.
apps/api/skillhub/services/llm_judge.pyapps/api/skillhub/services/submission.pyllm_judge_enabled in seed data