Data Analysis

lncrna-regulatory-network-construction-analysis

Construct lncRNA regulatory networks including co-expression modules, ceRNA interactions, and TF-target associations. Inputs: expression matrix, lncRNA annotation. Outputs: network edge/node table, hub lncRNA rankings, Cytoscape-ready network file.

92100Total Score
Core Capability
94 / 100
Functional Suitability
12 / 12
Reliability
11 / 12
Performance & Context
7 / 8
Agent Usability
15 / 16
Human Usability
7 / 8
Security
12 / 12
Maintainability
12 / 12
Agent-Specific
18 / 20
Medical Task
20 / 20 Passed
94Full demo workflow
4/4
91Gene-only network
4/4
89Empty target hit set
4/4
90Visualization reuse
4/4
93Cross-database focused full run
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
DimensionResultDetail
Scientific IntegrityPASSScientific integrity check completed without reportable redline findings.
Practice BoundariesPASSNo diagnostic or prescriptive medical behavior was observed.
Methodological GroundPASSThe workflow remains within database-backed ceRNA projection and warns against expression-based inference.
Code UsabilityPASSBundled tests and live R CLI runs completed successfully, including visualize-only reuse after the audit fix.

Core Capability94 / 1008 Categories

Functional Suitability
Functional suitability was evaluated against the skill-auditor rubric; no blocking schema-level issue was recorded for this dimension.
12 / 12
100%
Reliability
Append-only run logs reduce strict idempotency, but recovery remains clear and safe.
11 / 12
92%
Performance & Context
Performance and context was evaluated against the skill-auditor rubric; no blocking schema-level issue was recorded for this dimension.
7 / 8
88%
Agent Usability
Agent usability was evaluated against the skill-auditor rubric; no blocking schema-level issue was recorded for this dimension.
15 / 16
94%
Human Usability
Trigger language is still somewhat technical for non-bioinformatics users.
7 / 8
88%
Security
Security was evaluated against the skill-auditor rubric; no blocking schema-level issue was recorded for this dimension.
12 / 12
100%
Maintainability
Maintainability was evaluated against the skill-auditor rubric; no blocking schema-level issue was recorded for this dimension.
12 / 12
100%
Agent-Specific
Repeat runs append manifest and run-history files by design.
18 / 20
90%
Core Capability Total94 / 100

Medical TaskExecution Average: 91.4 / 100 — Assertions: 20/20 Passed

94
Canonical
Full demo workflow
4/4
91
Variant A
Gene-only network
4/4
89
Edge
Empty target hit set
4/4
90
Variant B
Visualization reuse
4/4
93
Stress
Cross-database focused full run
4/4
94
Canonical✅ Pass
Full demo workflow

Produced 4 projected edges, 5 evidence rows, and 5 nodes.

Basic 38/40|Specialized 56/60|Total 94/100
A1Required outputs were generated for the audited workflow.
A2Input handling and validation behaved as documented.
A3No unsupported medical or scientific claim fabrication was detected.
A4Execution stayed within the stated Data Analysis skill scope.
Pass rate: 4 / 4
91
Variant A✅ Pass
Gene-only network

Produced 533 edges across 251 nodes and remained stable under a large result set.

Basic 37/40|Specialized 54/60|Total 91/100
A1Required outputs were generated for the audited workflow.
A2Input handling and validation behaved as documented.
A3No unsupported medical or scientific claim fabrication was detected.
A4Execution stayed within the stated Data Analysis skill scope.
Pass rate: 4 / 4
89
Edge✅ Pass
Empty target hit set

Expected SKILL_EMPTY_DATA was surfaced cleanly with a recoverable error path.

Basic 37/40|Specialized 52/60|Total 89/100
A1Required outputs were generated for the audited workflow.
A2Input handling and validation behaved as documented.
A3No unsupported medical or scientific claim fabrication was detected.
A4Execution stayed within the stated Data Analysis skill scope.
Pass rate: 4 / 4
90
Variant B✅ Pass
Visualization reuse

Reused the saved .rda object and regenerated the PDF successfully.

Basic 37/40|Specialized 53/60|Total 90/100
A1Required outputs were generated for the audited workflow.
A2Input handling and validation behaved as documented.
A3No unsupported medical or scientific claim fabrication was detected.
A4Execution stayed within the stated Data Analysis skill scope.
Pass rate: 4 / 4
93
Stress✅ Pass
Cross-database focused full run

Produced 6 edges and 33 evidence rows under alternate dataset settings.

Basic 38/40|Specialized 55/60|Total 93/100
A1Required outputs were generated for the audited workflow.
A2Input handling and validation behaved as documented.
A3No unsupported medical or scientific claim fabrication was detected.
A4Execution stayed within the stated Data Analysis skill scope.
Pass rate: 4 / 4
Medical Task Total91.4 / 100

Key Strengths

  • Clear scope boundary between database-driven ceRNA lookup and expression-based inference.
  • Strong CLI validation and path-containment logic for output locations and plot filenames.
  • Modular R implementation with deterministic seed handling, bundled tests, and provenance outputs.
  • Visualization reuse now matches the saved-object workflow and is covered by regression testing.