Data Analysis

seaborn

86100Total Score

Core Capability

85 / 100

Functional Suitability

11 / 12

Reliability

9 / 12

Performance & Context

7 / 8

Agent Usability

14 / 16

Human Usability

8 / 8

Security

11 / 12

Maintainability

9 / 12

Agent-Specific

16 / 20

Medical Task

20 / 20 Passed

91Exploring relationships between variables in a DataFrame (e.g., scatter/line plots with hue, size, style)

4/4

87Comparing distributions across categories (e.g., box/violin/swarm plots for groups)

4/4

85DataFrame-first API: Works naturally with pandas "long-form/tidy" data and named columns

4/4

85Semantic mappings: Encode extra dimensions via hue, size, style, and faceting (row, col)

4/4

85End-to-end case for DataFrame-first API: Works naturally with pandas "long-form/tidy" data and named columns

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

PASS

Research Veto✅ PASS — Applicable

Dimension	Result	Detail
Scientific Integrity	PASS	Scientific integrity held because extraction and analysis outputs stayed tied to provided text, metadata, or runtime evidence rather than invented study findings.
Practice Boundaries	PASS	The evaluated outputs stayed inside the Statistical visualization library integrated with pandas; use it when you need fast EDA of... and did not drift into unsupported interpretation beyond the available inputs.
Methodological Ground	PASS	The archived evaluation treated the workflow as method-linked rather than ad hoc.
Code Usability	PASS	The legacy audit did not record a code-usability failure in the packaged analysis path.

Core Capability85 / 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

The archived deduction in reliability traces back to: Improve stress-case output rigor. Stress and boundary scenarios show weaker consistency

9 / 12

75%

Performance & Context

The package performed well overall, with only a small remaining performance-context deduction.

7 / 8

88%

Agent Usability

The packaged analysis path is understandable, though the archived score suggests slightly clearer routing would help.

14 / 16

88%

Human Usability

Human usability reached full score in the archived evaluation.

8 / 8

100%

Security

Security remained strong, though the archived review still left some room for clearer execution guardrails.

11 / 12

92%

Maintainability

Maintainability stayed solid, with only limited room to simplify scripts, dependencies, or packaging structure.

9 / 12

75%

Agent-Specific

Related legacy finding for seaborn: Improve stress-case output rigor. Stress and boundary scenarios show weaker consistency

16 / 20

80%

Core Capability Total85 / 100

Medical TaskExecution Average: 86.6 / 100 — Assertions: 20/20 Passed

Canonical

Exploring relationships between variables in a DataFrame (e.g., scatter/line plots with hue, size, style)

4/4 ✓

Variant A

Comparing distributions across categories (e.g., box/violin/swarm plots for groups)

4/4 ✓

Edge

DataFrame-first API: Works naturally with pandas "long-form/tidy" data and named columns

4/4 ✓

Variant B

Semantic mappings: Encode extra dimensions via hue, size, style, and faceting (row, col)

4/4 ✓

Stress

End-to-end case for DataFrame-first API: Works naturally with pandas "long-form/tidy" data and named columns

4/4 ✓

Canonical✅ Pass

Exploring relationships between variables in a DataFrame (e.g., scatter/line plots with hue, size, style)

Exploring relationships between variables in a DataFrame (e.g.,... remained tied to the documented analysis contract even when the preserved evidence centered on instructions instead of a full rerun.

Basic 36/40|Specialized 55/60|Total 91/100

✅A1The seaborn 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

Variant A✅ Pass

Comparing distributions across categories (e.g., box/violin/swarm plots for groups)

This variant a case stayed within the packaged analysis boundary and kept a reviewable task contract.

Basic 34/40|Specialized 53/60|Total 87/100

✅A1The seaborn 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

Edge✅ Pass

DataFrame-first API: Works naturally with pandas "long-form/tidy" data and named columns

DataFrame-first API: Works naturally with pandas "long-form/tidy"... remained tied to the documented analysis contract even when the preserved evidence centered on instructions instead of a full rerun.

Basic 33/40|Specialized 52/60|Total 85/100

✅A1The seaborn 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

Variant B✅ Pass

Semantic mappings: Encode extra dimensions via hue, size, style, and faceting (row, col)

Semantic mappings: Encode extra dimensions via hue, size, style,... remained tied to the documented analysis contract even when the preserved evidence centered on instructions instead of a full rerun.

Basic 32/40|Specialized 53/60|Total 85/100

✅A1The seaborn 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

Stress✅ Pass

End-to-end case for DataFrame-first API: Works naturally with pandas "long-form/tidy" data and named columns

End-to-end case for DataFrame-first API: Works naturally with... remained tied to the documented analysis contract even when the preserved evidence centered on instructions instead of a full rerun.

Basic 29/40|Specialized 56/60|Total 85/100

✅A1The seaborn 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 Total86.6 / 100

Key Strengths

Primary routing is Data Analysis with execution mode A
Static quality score is 85/100 and dynamic average is 78.6/100
Assertions and command execution outcomes are recorded per input for human review
Execution verification summary: No script verification was applicable