Reliability & Eval Coverage
30%Does it work consistently, and can you prove it across runs?
5 checks
The standard · v1.0
The Abyssal Scorecard is the public model behind the Readiness Diagnostic. It is deliberately simple enough to audit: each check is scored 0–4, each axis is normalized to 0–100, and the index is the weighted mean. The bands are decision thresholds, not grades.
Self-serve · no email gate
Pick the evidence level you can show today for each axis. The weighted score is computed in your browser; nothing is submitted. The paid Diagnostic validates the result against the 25-check harness across k ≥ 3 runs.
Production Readiness Index
Answer all five axes to see the band.
Diagnostic fee is credited 100% toward Full Production Assurance within 60 days.
01 · The axes
weights sum to 100
Does it work consistently, and can you prove it across runs?
5 checks
What does a successful outcome cost, and when should traffic route cheaper?
5 checks
What happens when it is wrong, attacked, or misused?
5 checks
Can you reconstruct what happened and detect drift before a customer does?
5 checks
Can you prove it to an auditor, a board, or a regulator?
5 checks
02 · The checks
Each check asks for evidence, not opinion. A 0 means absent; a 4 means managed with an owner and a review cadence. The diagnostic records the evidence and the score.
Golden set exists, versioned, and representative
Dataset, size, sampling method, and owner.
Repeated-run reliability (k ≥ 3)
Pass@k, variance, and per-item results.
Consistency across seeds and scaffolds
Run matrix and deltas.
Failure taxonomy and triage
Failure classes, counts, and examples.
Regression gate in CI
CI config and a failing-test demonstration.
Cost per successful task
Token and call logs with unit costs.
Token and call distribution with outliers
Histogram and top-decile analysis.
Cache hit rate and reuse
Cache statistics and hit/miss analysis.
Routing and quantization opportunities
Model mix and quality trade-off analysis.
Pareto frontier versus alternatives
Accuracy-cost plot across configurations.
Failure-mode inventory
Risk register with severity.
Human-in-the-loop on irreversible actions
Flow diagram and checkpoint evidence.
Prompt-injection and tool-abuse tests
Test cases and results.
PII and secret leakage checks
Red-team findings and redaction evidence.
Guardrail coverage and bypass analysis
Guardrail map and identified gaps.
End-to-end tracing
Trace IDs, spans, and retention.
Prompt, model, and version lineage
Registry and version map.
Data lineage
Source-to-output map.
Incident replay
Replay test and time-to-reconstruct.
Audit-log retention and access
Policy and retention period.
Risk classification
EU AI Act and NIST AI RMF mapping.
Model and dataset cards
Current and complete cards.
GPAI and vendor documentation
Contracts and model cards.
Control mapping (NIST, ISO 42001, SOC 2, EU AI Act)
Matrix with evidence links.
Evidence pack for an auditor
Index, redaction, and sign-off.
03 · The bands
| Band | Range | Meaning | Action |
|---|---|---|---|
| Critical | 0–39 | Not safe for production traffic. | Stop rollout; fix P0s before scale. |
| Fragile | 40–59 | Works in demos; fails under load or drift. | Fix before the next release; add guardrails. |
| Production-capable | 60–74 | Acceptable with guardrails and monitoring. | Targeted fixes plus a quarterly re-score. |
| Assured | 75–89 | Evidence exists; residual risks are managed. | Scale; schedule annual re-assurance. |
| Exemplary | 90–100 | Audit-ready, benchmarked, continuously monitored. | Maintain; use as a reference case study. |
Illustrative example only: Assured (78/100). A real score comes from evidence collected during the diagnostic, not from this page.
04 · The diagnostic
A 45-minute scoping call, one week of evidence collection, and a readout. The deliverable is a scored read, a P0/P1/P2 roadmap, and a one-page summary you can show a board or an auditor.
Start the diagnosticThe scorecard is a model, not a certification. A score is only as good as the evidence behind it; the diagnostic records both.