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Verdict: HEALTHY on baseline. 88.0% success (89.8% excluding 2 intentional credit-limit tests). Every real failure is a copilot-engine driver failure β for the 7th consecutive audit. Zero agent-logic failures, zero missing-tools/data, zero MCP failures, zero novel anomalies. Non-copilot engines were perfect.
Window: partial ~11.5h (09:30β21:05Z). 334 run dirs enumerated; 100 fully downloaded, 234 empty due to the bridge 120s cap (known partial-window pattern). Stats below are the 100 complete runs.
π Key Metrics
Metric
Value
Runs (complete)
100
Success / Failure
88 / 12
Success rate
88.0% (89.8% ex-2-intentional)
Missing tools / data / MCP / noop
0 / 0 / 0 / 0
Novel anomalies
0
AIC (cost units)
4,361
Tokens (in+out)
5.85M (5.12M in / 0.73M out)
Action minutes
1,006
Engine health
Engine
Runs
Fail
Rate
copilot
43
11
74.4% (76.2% ex-intentional)
pi
33
0
100%
claude
15
0
100%
codex
6
0
100%
gemini
1
0
100%
antigravity
1
0
100%
The failure surface is entirely copilot. Every other engine ran clean.
π Trends
Workflow Health (30 days)
Success rate holds in its stable ~86β90% band. Today's 88.0% sits squarely on the multi-week baseline β no degradation, no spike. The red (failure) bars remain small and, as every audit since 07-04, are composed exclusively of copilot 0-turn driver failures rather than agent-logic errors.
Token Usage (reporting-gap days omitted)
Daily token volume (5.85M this partial window) tracks the 7-day moving average with no outlier. Many historical days show gaps because metrics.TokenUsage reports 0 fleet-wide; the values plotted come from the reliable token_usage_summary fallback.
π§ Failure clustering (all 12)
All failures map to existing known-issues β expand for detail
Intentional (2) β expected, excluded from health rate:
Daily Max Ai Credits Test, Daily Credit Limit Test
copilot driver failures (10 real) β all 0-turn at a copilot driver step:
The longrun failures (30m/21m, AIC 142β156) burned real budget β the agent did the work, then the Execute GitHub Copilot CLI step exited non-zero on export/finalize. This is the copilot-SDK driver signature, not an agent-logic problem.
β οΈ New infrastructure observation: turns-reporting-gap
metrics.Turns is now 0 for all 100 runs including successes β not just metrics.TokenUsage. This breaks the long-used "0-turn β pre-agent driver failure" heuristic, since Turns=0 is now indistinguishable between healthy and failed runs. This audit classified failures by failed-step + AIC instead. token_usage_summary remains authoritative (5.85M). Logged under token-usage-reporting-gap.
β Recommendations
[medium] Fix the turns/token metric population. Populate metrics.Turns and metrics.TokenUsage from token_usage_summary (which is correct), or document that consumers must read token_usage_summary + failed-step β not metrics.*. Evidence: 100/100 runs have run.Turns=0 and metrics.TokenUsage=0 while token_usage_summary sums to 5.12M input.
[high] Root-cause the copilot CLI export/exit path. copilot is the sole failure source (76.2% ex-intentional) for the 7th straight audit; several fails burn AIC 52β156 before exiting non-zero. As mitigation, consider migrating the most-affected daily reporters to claude/pi (both 100% today). Evidence: copilot 32/42 vs pi 33/33, claude 15/15, codex 6/6.
[low] Smoke CI chronic red on push/main (smoke-ci-copilot-cli-100pct-fail-on-push, now recur 7) continues to color the health dashboard red on main with no signal value β either fix or suppress from the main-branch health view.
π° Top cost runs (context)
All top-cost runs are claude read-only reporters at normal levels β no cost anomaly:
Daily Code Metrics (AIC 330), Claude Code User Docs Reviewer (267), GitHub MCP Remote Server Tools Report (265). PR Sous Chef ran 23/23 = 100%.
References:
Β§29205558650 β Smoke Copilot Small (copilot driver fail)
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π Agentic Workflow Audit β 2026-07-12
Verdict: HEALTHY on baseline. 88.0% success (89.8% excluding 2 intentional credit-limit tests). Every real failure is a copilot-engine driver failure β for the 7th consecutive audit. Zero agent-logic failures, zero missing-tools/data, zero MCP failures, zero novel anomalies. Non-copilot engines were perfect.
π Key Metrics
Engine health
The failure surface is entirely copilot. Every other engine ran clean.
π Trends
Workflow Health (30 days)
Success rate holds in its stable ~86β90% band. Today's 88.0% sits squarely on the multi-week baseline β no degradation, no spike. The red (failure) bars remain small and, as every audit since 07-04, are composed exclusively of copilot 0-turn driver failures rather than agent-logic errors.
Token Usage (reporting-gap days omitted)
Daily token volume (5.85M this partial window) tracks the 7-day moving average with no outlier. Many historical days show gaps because
metrics.TokenUsagereports 0 fleet-wide; the values plotted come from the reliabletoken_usage_summaryfallback.π§ Failure clustering (all 12)
All failures map to existing known-issues β expand for detail
Intentional (2) β expected, excluded from health rate:
Daily Max Ai Credits Test,Daily Credit Limit Testcopilot driver failures (10 real) β all 0-turn at a copilot driver step:
smoke-ci-copilot-cli-100pct-fail-on-push(recur 7)copilot-sdk-driver-failurescopilot-sdk-driver-failurescopilot-sdk-driver-failurescopilot-sdk-driver-failurescopilot-sdk-driver-failurescopilot-sdk-driver-failureschroot-node-not-available(recur 12)safe-output-partial-failure-intoleranceThe longrun failures (30m/21m, AIC 142β156) burned real budget β the agent did the work, then the
Execute GitHub Copilot CLIstep exited non-zero on export/finalize. This is the copilot-SDK driver signature, not an agent-logic problem.metrics.Turnsis now 0 for all 100 runs including successes β not justmetrics.TokenUsage. This breaks the long-used "0-turn β pre-agent driver failure" heuristic, since Turns=0 is now indistinguishable between healthy and failed runs. This audit classified failures by failed-step + AIC instead.token_usage_summaryremains authoritative (5.85M). Logged undertoken-usage-reporting-gap.β Recommendations
[medium] Fix the turns/token metric population. Populate
metrics.Turnsandmetrics.TokenUsagefromtoken_usage_summary(which is correct), or document that consumers must readtoken_usage_summary+ failed-step β notmetrics.*. Evidence: 100/100 runs haverun.Turns=0andmetrics.TokenUsage=0whiletoken_usage_summarysums to 5.12M input.[high] Root-cause the copilot CLI export/exit path. copilot is the sole failure source (76.2% ex-intentional) for the 7th straight audit; several fails burn AIC 52β156 before exiting non-zero. As mitigation, consider migrating the most-affected daily reporters to claude/pi (both 100% today). Evidence: copilot 32/42 vs pi 33/33, claude 15/15, codex 6/6.
[low] Smoke CI chronic red on push/main (
smoke-ci-copilot-cli-100pct-fail-on-push, now recur 7) continues to color the health dashboard red onmainwith no signal value β either fix or suppress from the main-branch health view.π° Top cost runs (context)
All top-cost runs are claude read-only reporters at normal levels β no cost anomaly:
Daily Code Metrics (AIC 330), Claude Code User Docs Reviewer (267), GitHub MCP Remote Server Tools Report (265).
PR Sous Chefran 23/23 = 100%.References:
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