Data Analysis

pyopenms-skill

86100Total Score

Core Capability

85 / 100

Functional Suitability

11 / 12

Reliability

9 / 12

Performance & Context

8 / 8

Agent Usability

14 / 16

Human Usability

8 / 8

Security

9 / 12

Maintainability

9 / 12

Agent-Specific

17 / 20

Medical Task

20 / 20 Passed

91Converting, validating, or batch-processing mass spectrometry files (e.g., mzML, mzXML, MGF) as part of a pipeline

4/4

87Cleaning raw spectra before downstream analysis (smoothing, baseline correction, denoising, peak picking)

4/4

85MS File I/O: Read/write common MS formats (mzML, mzXML, MGF)

4/4

85Signal Processing: Smoothing, baseline correction, filtering, and peak picking

4/4

85End-to-end case for MS File I/O: Read/write common MS formats (mzML, mzXML, MGF)

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	No scientific-integrity problem was surfaced because the package did not claim more than the available records, article text, or script evidence supported.
Practice Boundaries	PASS	Practice boundaries held because the package remained focused on Comprehensive tool for computational mass spectrometry using PyOpenMS rather than overclaiming what the records supported.
Methodological Ground	PASS	The legacy review kept the package aligned with its named analysis library, data structure, or processing workflow.
Code Usability	PASS	The archived review preserved a usable code path with named scripts, expected inputs, and a recognizable output contract.

Core Capability85 / 100 — 8 Categories

Functional Suitability

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

11 / 12

92%

Reliability

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

9 / 12

75%

Performance & Context

No point loss was recorded for performance context in the legacy audit.

8 / 8

100%

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

A modest security gap remained in the archived evaluation despite otherwise controlled workflow behavior.

9 / 12

75%

Maintainability

The archived review treated the package as maintainable, while still preserving some room for cleanup.

9 / 12

75%

Agent-Specific

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

17 / 20

85%

Core Capability Total85 / 100

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

Canonical

Converting, validating, or batch-processing mass spectrometry files (e.g., mzML, mzXML, MGF) as part of a pipeline

4/4 ✓

Variant A

Cleaning raw spectra before downstream analysis (smoothing, baseline correction, denoising, peak picking)

4/4 ✓

Edge

MS File I/O: Read/write common MS formats (mzML, mzXML, MGF)

4/4 ✓

Variant B

Signal Processing: Smoothing, baseline correction, filtering, and peak picking

4/4 ✓

Stress

End-to-end case for MS File I/O: Read/write common MS formats (mzML, mzXML, MGF)

4/4 ✓

Canonical✅ Pass

Converting, validating, or batch-processing mass spectrometry files (e.g., mzML, mzXML, MGF) as part of a pipeline

Converting, validating, or batch-processing mass spectrometry files... 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 pyopenms-skill 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

Cleaning raw spectra before downstream analysis (smoothing, baseline correction, denoising, peak picking)

Cleaning raw spectra before downstream analysis (smoothing,... remained an analysis-style extraction path whose value came from structured data capture rather than a freeform narrative response.

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

✅A1The pyopenms-skill 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

MS File I/O: Read/write common MS formats (mzML, mzXML, MGF)

MS File I/O: Read/write common MS formats (mzML, mzXML, MGF) 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 pyopenms-skill 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

Signal Processing: Smoothing, baseline correction, filtering, and peak picking

Signal Processing: Smoothing, baseline correction, filtering, and... remained an analysis-style extraction path whose value came from structured data capture rather than a freeform narrative response.

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

✅A1The pyopenms-skill 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 MS File I/O: Read/write common MS formats (mzML, mzXML, MGF)

End-to-end case for MS File I/O: Read/write common MS formats... 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 pyopenms-skill 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 B
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: Script verification 0/1; adjustment=0. process_ms.py: rc=1