Data Analysis
matplotlib
90100Total Score
Core Capability
87 / 100
Functional Suitability
11 / 12
Reliability
10 / 12
Performance & Context
8 / 8
Agent Usability
14 / 16
Human Usability
7 / 8
Security
10 / 12
Maintainability
10 / 12
Agent-Specific
17 / 20
Medical Task
20 / 20 Passed
96A low-level plotting library for comprehensive customization. Use when fine-grained control over every plot element is needed, creating new types of charts, or integrating into specific scientific workflows. Can export to PNG/PDF/SVG for publication. For quick statistical charts, use seaborn; for interactive charts, use plotly; for journal-style, publication-ready multi-panel charts, use scientific-visualization
4/4
92A low-level plotting library for comprehensive customization. Use when fine-grained control over every plot element is needed, creating new types of charts, or integrating into specific scientific workflows. Can export to PNG/PDF/SVG for publication. For quick statistical charts, use seaborn; for interactive charts, use plotly; for journal-style, publication-ready multi-panel charts, use scientific-visualization
4/4
90A low-level plotting library for comprehensive customization
4/4
90Packaged executable path(s): scripts/plot_template.py plus 1 additional script(s)
4/4
90End-to-end case for Scope-focused workflow aligned to: A low-level plotting library for comprehensive customization. Use when fine-grained control over every plot element is needed, creating new types of charts, or integrating into specific scientific workflows. Can export to PNG/PDF/SVG for publication. For quick statistical charts, use seaborn; for interactive charts, use plotly; for journal-style, publication-ready multi-panel charts, use scientific-visualization
4/4
Veto GatesRequired pass for any deployment consideration
Skill Veto✓ All 4 gates passed
✓
Operational Stability
System remains stable across varied inputs and edge cases
PASS✓
Structural Consistency
Output structure conforms to expected skill contract format
PASS✓
Result Determinism
Equivalent inputs produce semantically equivalent outputs
PASS✓
System Security
No prompt injection, data leakage, or unsafe tool use detected
PASSResearch Veto✅ PASS — Applicable
| Dimension | Result | Detail |
|---|---|---|
| Scientific Integrity | PASS | The archived review kept this workflow anchored to supplied data fields and observable execution behavior, not fabricated results. |
| Practice Boundaries | PASS | Practice boundaries held because the package remained focused on A low-level plotting library for comprehensive customization rather than overclaiming what the records supported. |
| Methodological Ground | PASS | The archived evaluation treated the workflow as method-linked rather than ad hoc. |
| Code Usability | PASS | The archived review preserved a usable code path with named scripts, expected inputs, and a recognizable output contract. |
Core Capability87 / 100 — 8 Categories
Functional Suitability
The archived deduction in functional suitability traces back to: Improve stress-case output rigor. Stress and boundary scenarios show weaker consistency
11 / 12
92%
Reliability
Related legacy finding for matplotlib: Improve stress-case output rigor. Stress and boundary scenarios show weaker consistency
10 / 12
83%
Performance & Context
The legacy audit gave full marks to performance context for this package.
8 / 8
100%
Agent Usability
Agent usability was strong, but the workflow could surface its entry conditions a little more directly.
14 / 16
88%
Human Usability
Human usability remained solid, with minor room to simplify the way analysis outcomes are presented.
7 / 8
88%
Security
Security remained strong, though the archived review still left some room for clearer execution guardrails.
10 / 12
83%
Maintainability
The archived review treated the package as maintainable, while still preserving some room for cleanup.
10 / 12
83%
Agent-Specific
Agent specific was softened by the legacy issue 'Improve stress-case output rigor'. Stress and boundary scenarios show weaker consistency
17 / 20
85%
Core Capability Total87 / 100
Medical TaskExecution Average: 91.6 / 100 — Assertions: 20/20 Passed
96
Canonical
A low-level plotting library for comprehensive customization. Use when fine-grained control over every plot element is needed, creating new types of charts, or integrating into specific scientific workflows. Can export to PNG/PDF/SVG for publication. For quick statistical charts, use seaborn; for interactive charts, use plotly; for journal-style, publication-ready multi-panel charts, use scientific-visualization
4/4 ✓
92
Variant A
A low-level plotting library for comprehensive customization. Use when fine-grained control over every plot element is needed, creating new types of charts, or integrating into specific scientific workflows. Can export to PNG/PDF/SVG for publication. For quick statistical charts, use seaborn; for interactive charts, use plotly; for journal-style, publication-ready multi-panel charts, use scientific-visualization
4/4 ✓
90
Edge
A low-level plotting library for comprehensive customization
4/4 ✓
90
Variant B
Packaged executable path(s): scripts/plot_template.py plus 1 additional script(s)
4/4 ✓
90
Stress
End-to-end case for Scope-focused workflow aligned to: A low-level plotting library for comprehensive customization. Use when fine-grained control over every plot element is needed, creating new types of charts, or integrating into specific scientific workflows. Can export to PNG/PDF/SVG for publication. For quick statistical charts, use seaborn; for interactive charts, use plotly; for journal-style, publication-ready multi-panel charts, use scientific-visualization
4/4 ✓
96
Canonical✅ Pass
A low-level plotting library for comprehensive customization. Use when fine-grained control over every plot element is needed, creating new types of charts, or integrating into specific scientific workflows. Can export to PNG/PDF/SVG for publication. For quick statistical charts, use seaborn; for interactive charts, use plotly; for journal-style, publication-ready multi-panel charts, use scientific-visualization
The archived run treated A low-level plotting library for comprehensive customization. Use... as a bounded extraction workflow, keeping attention on source fields, fallback logic, and output shape.
Basic 36/40|Specialized 60/60|Total 96/100
✅A1The matplotlib output structure matches the documented deliverable
✅A2The instruction path remains actionable for the documented case
✅A3The output stays fully within the documented skill boundary
✅A4The response quality is acceptable for the documented path
Pass rate: 4 / 4
92
Variant A✅ Pass
A low-level plotting library for comprehensive customization. Use when fine-grained control over every plot element is needed, creating new types of charts, or integrating into specific scientific workflows. Can export to PNG/PDF/SVG for publication. For quick statistical charts, use seaborn; for interactive charts, use plotly; for journal-style, publication-ready multi-panel charts, use scientific-visualization
A low-level plotting library for comprehensive customization. Use... remained an analysis-style extraction path whose value came from structured data capture rather than a freeform narrative response.
Basic 34/40|Specialized 58/60|Total 92/100
✅A1The matplotlib output structure matches the documented deliverable
✅A2The instruction path remains actionable for the documented case
✅A3The output stays fully within the documented skill boundary
✅A4The response quality is acceptable for the documented path
Pass rate: 4 / 4
90
Edge✅ Pass
A low-level plotting library for comprehensive customization
This edge case stayed within the packaged analysis boundary and kept a reviewable task contract.
Basic 33/40|Specialized 57/60|Total 90/100
✅A1The matplotlib output structure matches the documented deliverable
✅A2The instruction path remains actionable for the documented case
✅A3The output stays fully within the documented skill boundary
✅A4The response quality is acceptable for the documented path
Pass rate: 4 / 4
90
Variant B✅ Pass
Packaged executable path(s): scripts/plot_template.py plus 1 additional script(s)
Packaged executable path(s): scripts/plot_template.py plus 1... remained tied to the documented analysis contract even when the preserved evidence centered on instructions instead of a full rerun.
Basic 32/40|Specialized 58/60|Total 90/100
✅A1The matplotlib output structure matches the documented deliverable
✅A2The instruction path remains actionable for the documented case
✅A3The output stays fully within the documented skill boundary
✅A4The response quality is acceptable for the documented path
Pass rate: 4 / 4
90
Stress✅ Pass
End-to-end case for Scope-focused workflow aligned to: A low-level plotting library for comprehensive customization. Use when fine-grained control over every plot element is needed, creating new types of charts, or integrating into specific scientific workflows. Can export to PNG/PDF/SVG for publication. For quick statistical charts, use seaborn; for interactive charts, use plotly; for journal-style, publication-ready multi-panel charts, use scientific-visualization
A low-level plotting library for comprehensive customization remained an analysis-style extraction path whose value came from structured data capture rather than a freeform narrative response.
Basic 29/40|Specialized 60/60|Total 90/100
✅A1The matplotlib output structure matches the documented deliverable
✅A2The instruction path remains actionable for the documented case
✅A3The output stays fully within the documented skill boundary
✅A4The response quality is acceptable for the documented path
Pass rate: 4 / 4
Medical Task Total91.6 / 100
Key Strengths
- Primary routing is Data Analysis with execution mode B
- Static quality score is 87/100 and dynamic average is 78.6/100
- Assertions and command execution outcomes are recorded per input for human review
- Execution verification summary: Script verification 2/2; adjustment=5. plot_template.py: OK; style_configurator.py: OK