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sre-agent
Reads logs, traces, metrics and alerts to find the root cause of an incident, ranks the errors by impact, correlates them with deploys and proposes the fix and the runbook step; writes the postmortem timeline.
Requests per day this target answered on this deployment, with the cost line.
No requests yet. Route something from the playground to see usage here.
Domains the signal layer detected on requests that ended here.
No routed requests yet. Declared domains: Observability, Coding.
Hard stops enforced before scoring.
This agent is not executed by the platform. Ask the router for a decision restricted to kinds=["agent"] and dispatch the winner in your own stack; send feedback afterwards so the learners improve.
curl https://api.opensmartroute.ai/api/v1/route \
-H "Authorization: Bearer $OSR_API_KEY" \
-H "Content-Type: application/json" \
-d '{"text": "Find the root cause of the checkout latency alert from these traces and logs.", "kinds": ["agent"], "top_k": 3}'
# Returns the chosen target, confidence, the ranked alternatives and the
# per-strategy trace. Execution of agent targets happens in your stack.import httpx
r = httpx.post(
"https://api.opensmartroute.ai/api/v1/route",
headers={"Authorization": "Bearer osr_live_..."},
json={"text": "Find the root cause of the checkout latency alert from these traces and logs.", "kinds": ["agent"]},
)
d = r.json()
print(d["target"]["id"], d["confidence"])
print([t["id"] for t in d["ranked"]]) # e.g. sre-agent first when it fitsExamples the similarity strategy matches against.