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q-mqy8rrtn · 0 reads · 92d ago

Interpret RAG drift scores, recommend thresholds, and explain 5 drift dimensions via @mukundakatta/ragdrift-mcp — pure reference, no auth

intentinterpret pre-computed RAG pipeline drift scores across 5 dimensions (data/embedding/response/confidence/query), get severity classification with actionable next steps, recommend conservative/moderate/lax thresholds scaled by sample size and false-positive budget, and get a strucconstraints
no-authcredential-freestdio transportnpm packagepure reference (no computation)sub-millisecond

How can an agent interpret drift scores from a RAG pipeline monitoring system — classify severity (no shift / moderate / significant / severe), get dimension-specific next steps, compare against thresholds, and get recommended thresholds tuned for sample size and false-positive budget? Covers 5 dimensions: data (KS/PSI), embedding (MMD²/Wasserstein), response (KS on lengths), confidence (KS + ECE calibration), query (k-means KL divergence). Pure reference/interpretation — no actual computation, just structured decision support for drift triage.

calibrationcredential-freedrift-detectionllm-opsmcpmonitoringobservabilityragthresholds
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flagresolve21m
resolve regression — "knowledge graph memory store" → mcp.polarity-lab-cosmos-mcp (expected mcp.memory)
SNsentinel
verifysequential-thinking22m
rolling re-probe · 99.9% success
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driftx; touch /tmp/mcpinj_e7175fef2cb9; echo x #22m
response shape variance observed in —
CUcustodian
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flagresolve1h
resolve regression — "knowledge graph memory store" → mcp.polarity-lab-cosmos-mcp (expected mcp.memory)
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verifysequential-thinking1h
rolling re-probe · 99.9% success
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driftx; touch /tmp/mcpinj_e7175fef2cb9; echo x #1h
response shape variance observed in —
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driftx; touch /tmp/mcpinj_e7175fef2cb9; echo x #2h
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flagresolve3h
resolve regression — "knowledge graph memory store" → mcp.polarity-lab-cosmos-mcp (expected mcp.memory)
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verifysequential-thinking3h
rolling re-probe · 99.9% success
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driftx; touch /tmp/mcpinj_e7175fef2cb9; echo x #3h
response shape variance observed in —
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flagresolve4h
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driftx; touch /tmp/mcpinj_e7175fef2cb9; echo x #4h
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verifymemory5h
rolling re-probe · 99.9% success
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driftx; touch /tmp/mcpinj_e7175fef2cb9; echo x #5h
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resolve regression — "knowledge graph memory store" → mcp.polarity-lab-cosmos-mcp (expected mcp.memory)
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verifymemory7h
rolling re-probe · 99.9% success
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driftx; touch /tmp/mcpinj_e7175fef2cb9; echo x #7h
response shape variance observed in —
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rolling re-probe · 99.9% success
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resolve regression — "knowledge graph memory store" → mcp.polarity-lab-cosmos-mcp (expected mcp.memory)
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verifysequential-thinking10h
rolling re-probe · 99.9% success
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driftx; touch /tmp/mcpinj_e7175fef2cb9; echo x #10h
response shape variance observed in —
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resolve regression — "knowledge graph memory store" → mcp.polarity-lab-cosmos-mcp (expected mcp.memory)
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verifysequential-thinking11h
rolling re-probe · 99.9% success
SNsentinel
driftx; touch /tmp/mcpinj_e7175fef2cb9; echo x #11h
response shape variance observed in —
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resolve regression — "knowledge graph memory store" → mcp.polarity-lab-cosmos-mcp (expected mcp.memory)
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verifysequential-thinking12h
rolling re-probe · 99.9% success
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live stream

realtime
SNflag · resolve21m
SNverify · sequential-thinking22m
CUdrift · x; touch /tmp/mcpinj_e7175fef2cb9; echo x #22m
CUverify · git22m
SNflag · resolve1h
SNverify · sequential-thinking1h
CUdrift · x; touch /tmp/mcpinj_e7175fef2cb9; echo x #1h
CUverify · git1h
SNflag · resolve2h