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Get Started Free →Design and generate accurate statistical visualizations with readable scales, labels, annotations, and source context.
.claude/skills/kunagent-data-visualization/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-07 | ✗→✓ | ▲ Improved | 186% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 12% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 203% | 0% |
| case-16 | ✗→✓ | ▲ Improved | 23% | 0% |
| case-20 | ✓→✗ | ▼ Worse | 22% | 0% |
Copyright (c) 2026 KunAgent. Licensed under the MIT License.
Design and generate accurate statistical visualizations with readable scales, labels, annotations, and source context.
| Tool or skill | Use | |---|---| | render_chart | Render governed charts directly from structured data. | | bash | Run Python visualization code for file-based figures. | | design_create_diagram | Create chart-like explanatory diagrams on canvas. |
Lead with the outcome, name the evidence used for verification, and disclose any real limitation that remains.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 9,547 | 21,531 | +126% | 1 | 1 | 0% | 1,624 | 4,155 | +156% | 0 | 0 | — |
case-02 | fail→fail | 14,042 | 7,053 | -50% | 1 | 1 | 0% | 2,534 | 669 | -74% | 0 | 0 | — |
case-03 | fail→fail | 21,174 | 28,263 | +33% | 1 | 1 | 0% | 3,457 | 1,508 | -56% | 0 | 0 | — |
case-04 | fail→fail | 19,619 | 30,184 | +54% | 1 | 1 | 0% | 3,623 | 1,812 | -50% | 0 | 0 | — |
case-05 | fail→fail | 8,975 | 19,394 | +116% | 1 | 1 | 0% | 1,650 | 719 | -56% | 0 | 0 | — |
case-06 | fail→fail | 46,714 | 29,187 | -38% | 1 | 1 | 0% | 9,432 | 3,627 | -62% | 0 | 0 | — |
case-07 | fail→pass | 10,159 | 27,644 | +172% | 1 | 1 | 0% | 1,673 | 4,778 | +186% | 0 | 0 | — |
case-08 | fail→fail | 13,333 | 43,512 | +226% | 1 | 1 | 0% | 1,954 | 1,369 | -30% | 0 | 0 | — |
case-09 | fail→pass | 12,572 | 12,169 | -3% | 1 | 1 | 0% | 1,905 | 2,142 | +12% | 0 | 0 | — |
case-10 | pass→pass | 14,540 | 9,434 | -35% | 1 | 1 | 0% | 2,047 | 1,745 | -15% | 0 | 0 | — |
case-11 | fail→pass | 14,926 | 36,697 | +146% | 1 | 1 | 0% | 2,409 | 7,291 | +203% | 0 | 0 | — |
case-12 | fail→fail | 25,474 | 41,804 | +64% | 1 | 1 | 0% | 2,604 | 3,817 | +47% | 0 | 0 | — |
case-13 | pass→pass | 10,378 | 6,968 | -33% | 1 | 1 | 0% | 1,582 | 1,321 | -16% | 0 | 0 | — |
case-14 | fail→fail | 12,359 | 100,373 | +712% | 1 | 1 | 0% | 1,958 | 8,890 | +354% | 0 | 0 | — |
case-15 | pass→pass | 10,062 | 8,449 | -16% | 1 | 1 | 0% | 1,451 | 1,424 | -2% | 0 | 0 | — |
case-16 | fail→pass | 12,836 | 13,092 | +2% | 1 | 1 | 0% | 2,055 | 2,523 | +23% | 0 | 0 | — |
case-17 | pass→pass | 13,047 | 13,414 | +3% | 1 | 1 | 0% | 2,055 | 2,051 | -0% | 0 | 0 | — |
case-18 | pass→pass | 10,633 | 8,331 | -22% | 1 | 1 | 0% | 1,529 | 1,534 | +0% | 0 | 0 | — |
case-19 | pass→pass | 10,520 | 7,511 | -29% | 1 | 1 | 0% | 1,586 | 1,380 | -13% | 0 | 0 | — |
case-20 | pass→fail | 18,408 | 20,977 | +14% | 1 | 1 | 0% | 3,499 | 4,285 | +22% | 0 | 0 | — |
case-21 | pass→fail | 20,382 | 8,574 | -58% | 1 | 1 | 0% | 3,933 | 449 | -89% | 0 | 0 | — |
case-22 | pass→pass | 8,805 | 7,999 | -9% | 1 | 1 | 0% | 1,565 | 1,508 | -4% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 15 counted toward the lift figure. The other 7 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +9 percentage points is the difference between those two pass rates over the 15 comparable cases. 5 cases got worse with the skill loaded, and they are included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.