Data Analysis

bioservices

87100Total Score

Core Capability

87 / 100

Functional Suitability

11 / 12

Reliability

10 / 12

Performance & Context

8 / 8

Agent Usability

14 / 16

Human Usability

8 / 8

Security

9 / 12

Maintainability

10 / 12

Agent-Specific

17 / 20

Medical Task

20 / 20 Passed

91You need to retrieve and combine biological data from multiple databases (e.g., UniProt + KEGG + GO) in one Python workflow

4/4

87You need cross-database identifier mapping (e.g., UniProt ↔ KEGG, KEGG compound ↔ ChEMBL) as part of downstream analysis

4/4

86Unified API for ~40+ bioinformatics services (single Python package, consistent patterns)

4/4

86Transparent protocol handling (REST and SOAP/WSDL)

4/4

86End-to-end case for Unified API for ~40+ bioinformatics services (single Python package, consistent patterns)

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 Unified Python access to 40+ bioinformatics web services and did not drift into unsupported interpretation beyond the available inputs.
Methodological Ground	PASS	Methodological grounding was preserved through the documented inputs, transformations, and expected artifacts.
Code Usability	PASS	The legacy audit did not record a code-usability failure in the packaged analysis path.

Core Capability87 / 100 — 8 Categories

Functional Suitability

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

11 / 12

92%

Reliability

Reliability was softened by the legacy issue '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

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

14 / 16

88%

Human Usability

The legacy audit gave full marks to human usability for this package.

8 / 8

100%

Security

The packaged workflow stayed safe overall, with only a small remaining deduction around boundary signaling.

9 / 12

75%

Maintainability

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

10 / 12

83%

Agent-Specific

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

17 / 20

85%

Core Capability Total87 / 100

Medical TaskExecution Average: 87.2 / 100 — Assertions: 20/20 Passed

Canonical

You need to retrieve and combine biological data from multiple databases (e.g., UniProt + KEGG + GO) in one Python workflow

4/4 ✓

Variant A

You need cross-database identifier mapping (e.g., UniProt ↔ KEGG, KEGG compound ↔ ChEMBL) as part of downstream analysis

4/4 ✓

Edge

Unified API for ~40+ bioinformatics services (single Python package, consistent patterns)

4/4 ✓

Variant B

Transparent protocol handling (REST and SOAP/WSDL)

4/4 ✓

Stress

End-to-end case for Unified API for ~40+ bioinformatics services (single Python package, consistent patterns)

4/4 ✓

Canonical✅ Pass

You need to retrieve and combine biological data from multiple databases (e.g., UniProt + KEGG + GO) in one Python workflow

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

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

✅A1The bioservices 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

You need cross-database identifier mapping (e.g., UniProt ↔ KEGG, KEGG compound ↔ ChEMBL) as part of downstream analysis

The archived run treated You need cross-database identifier mapping (e.g., UniProt ↔ KEGG,... as a bounded analysis workflow rather than a purely narrative instruction path.

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

✅A1The bioservices 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

Unified API for ~40+ bioinformatics services (single Python package, consistent patterns)

Unified API for ~40+ bioinformatics services (single Python... remained tied to the documented analysis contract even when the preserved evidence centered on instructions instead of a full rerun.

Basic 33/40|Specialized 53/60|Total 86/100

✅A1The bioservices 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

Transparent protocol handling (REST and SOAP/WSDL)

Transparent protocol handling (REST and SOAP/WSDL) remained tied to the documented analysis contract even when the preserved evidence centered on instructions instead of a full rerun.

Basic 32/40|Specialized 54/60|Total 86/100

✅A1The bioservices 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 Unified API for ~40+ bioinformatics services (single Python package, consistent patterns)

The archived run treated End-to-end case for Unified API for ~40+ bioinformatics services... as a bounded analysis workflow rather than a purely narrative instruction path.

Basic 29/40|Specialized 57/60|Total 86/100

✅A1The bioservices 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 Total87.2 / 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 0/4; adjustment=0. batch_id_converter.py: rc=1; compound_cross_reference.py: rc=1; pathway_analysis.py: rc=1; protein_analysis_workflow.py: rc=1