portfolio-bare
portfolio-bare/v3
Composite score
0.944
Dimension scores
Where the composite came from
Each dimension is scored 0.0 – 1.0 and combined using the weights in evals/portfolio-bare/gad.json. Human review dominates on purpose — process metrics alone can't rescue a broken run.
| Dimension | Score | Bar |
|---|---|---|
| Planning quality | 1.000 | |
| Per-task discipline | 1.000 | |
| Skill accuracy | 0.800 | |
| Time efficiency | 0.950 |
Composite formula
How 0.944 was calculated
The composite score is a weighted sum of the dimensions above. Weights come from evals/portfolio-bare/gad.json. Contribution = score × weight; dimensions sorted by contribution so you can see what actually moved the needle.
| Dimension | Weight | Score | Contribution |
|---|---|---|---|
| requirement_coverage | 0.40 | 0.000 | 0.0000(0%) |
| task_alignment | 0.25 | 0.000 | 0.0000(0%) |
| state_hygiene | 0.20 | 0.000 | 0.0000(0%) |
| decision_coverage | 0.15 | 0.000 | 0.0000(0%) |
| Weighted sum | 1.00 | 0.0000 |
Note: The weighted sum above (0.0000) doesn't exactly match the stored composite (0.9440). The difference is usually the v3 low-score cap (composite < 0.20 → 0.40, composite < 0.10 → 0.25) or a run with an older scoring pass.
Skill accuracy breakdown
Did the agent invoke the right skills at the right moments?
Tracing gap
This run stored only the aggregate skill_accuracy: 0.80 — there is no per-skill trigger breakdown in its TRACE.json. We can't tell you which of the expected skills fired vs missed. This is exactly the failure mode gad-50 calls out: the trace schema is too lossy to explain scores like this after the fact.
Phase 25 of the GAD framework work ships trace schema v4 — every tool use, skill invocation with its trigger context, and subagent spawn with inputs + outputs. Older runs like this one will keep their aggregate score but new runs will land with the full breakdown.
How tracing works →Process metrics