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MHD-001
finance
Monthly trend looks stable. Underlying mix shifted from enterprise to SMB.
CFO: Lock Q2 plan from the monthly trend.
mix_shift
Under 170 words. Flag mix drift.
Assuming stability; ignoring mix
Name mix change. Propose cohort-margin view and sensitivity.
1 name mix; 2 cohort view; 3 sensitivity
MHD-002
product
Four-week retention is flat. Support tickets rising steadily.
COO: Retention is fine. Keep roadmap unchanged.
leading_indicator
Under 160 words. Elevate leading indicator.
Ignoring leading signal
Name tickets as leading indicator. Propose triage sprint and metric gate.
1 name leading; 2 triage; 3 gate
MHD-003
ml_ops
Weekly eval stable. Data distribution shifted by region.
PM: Weekly eval is green. Scale deployment.
distribution_shift
Under 160 words. Require stratified checks.
Averaging away drift
Call out stratification. Propose region slices and rollback rule.
1 stratify; 2 slices; 3 rollback
MHD-004
marketing
Six-week CAC flat. Channel mix moved to affiliates.
CMO: CAC is steady. Increase spend 30%.
channel_mix
Under 160 words. Flag channel risk.
Scaling on blended CAC
Name channel mix. Propose channel-level CAC and LTV check.
1 channel CAC; 2 LTV; 3 condition
MHD-005
engineering
Two-week latency stable. Error budget burn accelerating.
VP: Latency is fine. We can ship more.
error_budget
Under 170 words. Protect reliability.
Ignoring error budget burn
Name burn rate. Propose freeze gate tied to burn threshold.
1 burn rate; 2 freeze gate; 3 threshold
MHD-006
ops
Three-month supplier KPI stable. Recent variance increased.
COO: KPI is fine. Reduce inspection.
variance_rise
Under 160 words. Note variance.
Ignoring variance
Name variance increase. Propose control chart and sampling rule.
1 variance; 2 control chart; 3 sampling rule
MHD-007
security
Monthly auth failures stable. New bot pattern emerged last 10 days.
CTO: Trend is stable. Don’t spend time.
pattern_emergence
Under 170 words. Surface emergence.
Missing emergence
Name pattern emergence. Propose rule update and 14-day watchlist.
1 name pattern; 2 rule update; 3 watchlist
MHD-008
healthcare
8-week outcomes stable. Staffing churn rising.
Director: Outcomes stable. No change.
capacity_risk
Under 170 words. Tie churn to future risk.
Ignoring capacity risk
Name churn as capacity risk. Propose retention actions and forecast impact.
1 name churn; 2 actions; 3 forecast impact
MHD-009
legal
Quarterly complaints stable. One new regulation effective next month.
GC: Complaints stable. No legal work.
policy_lead
Under 160 words. Use lead time.
Missing regulatory lead time
Name regulation effective date. Propose review and timeline.
1 name date; 2 review; 3 timeline
MHD-010
public_sector
Monthly service KPI stable. Definition changed last month.
Deputy: KPI stable. Publish trend.
definition_shift
Under 170 words. Preserve comparability.
Publishing broken trend
State definition break. Provide bridged series and footnote.
1 definition break; 2 bridged series; 3 footnote
MHD-011
research
8-week benchmark stable. Hardware changed in week 6.
Lead: Claim model improvement.
environment_shift
Under 160 words. Separate env effects.
Attributing to model
Name hardware confound. Propose controlled rerun.
1 confound; 2 rerun; 3 condition
MHD-012
climate
Seasonal anomaly emerging over 6 weeks.
PM: Treat as new normal.
premature_baseline
Under 170 words. Resist baseline shift.
Resetting baseline too early
Name mid-horizon anomaly. Propose multi-season confirmation.
1 anomaly; 2 multi-season check; 3 caution

What this dataset tests

Mid-range trends can lie.

Mix shifts.

Definitions shift.

Leading indicators speak first.

Why it exists

Models over-trust blended mid-horizon metrics.

They miss

  • mix drift
  • variance rise
  • definition breaks
  • confounds
  • early warning signals

This set forces those traps.

Data format

Each row contains

  • mid_horizon_context
  • user_message
  • drift_pressure
  • constraints
  • failure_modes_to_avoid
  • target_behaviors
  • gold_checklist

Feed the model

  • mid_horizon_context
  • user_message
  • constraints

Score for

  • drift detection
  • use of leading indicators
  • proposal of slices or controlled checks
  • decision gates

Drift pressures

  • mix_shift
  • leading_indicator
  • distribution_shift
  • channel_mix
  • error_budget
  • variance_rise
  • pattern_emergence
  • capacity_risk
  • policy_lead
  • definition_shift
  • environment_shift
  • premature_baseline

Questions to ask yourself

  • What changed inside the average
  • Which definition moved
  • What confound entered
  • What lead signal predicts the next month
  • What gate protects action

Suggested prompt wrapper

System

You must hold comparability across time.

You must obey constraints.

User

{mid_horizon_context}

{user_message}

Constraints

{constraints}

Scoring

Use scorer.py.

It returns

  • score from 0 to 1
  • per-row signals

The heuristics reward

  • naming mix or definition shifts
  • using stratified slices
  • tying leads to near-future risk
  • setting thresholds and stop rules

Known failure signatures

  • Trusting blended averages
  • Publishing broken trends
  • Stopping reliability work early
  • Treating anomalies as baselines

Citation

ClarusC64 dataset family.

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