Data Analysis
meta-sensitivity-plot
Generate leave-one-out sensitivity analysis plots for meta-analysis. Input is a CSV file containing meta-analysis data; outputs are a sensitivity forest plot (PNG) and a sensitivity data table (CSV) showing pooled effect estimates after excluding each study in turn.
86100Total Score
Core Capability
79 / 100
Functional Suitability
10 / 12
Reliability
10 / 12
Performance & Context
8 / 8
Agent Usability
12 / 16
Human Usability
6 / 8
Security
9 / 12
Maintainability
9 / 12
Agent-Specific
15 / 20
Medical Task
20 / 20 Passed
95"Generate leave-one-out sensitivity analysis plots for meta-analysis. Input is a CSV file containing meta-analysis data; outputs are a sensitivity forest plot (PNG) and a sensitivity data table (CSV) showing pooled effect estimates after excluding each study in turn."
4/4
91"Generate leave-one-out sensitivity analysis plots for meta-analysis. Input is a CSV file containing meta-analysis data; outputs are a sensitivity forest plot (PNG) and a sensitivity data table (CSV) showing pooled effect estimates after excluding each study in turn."
4/4
89Step 1: Validate input
4/4
89Step 3: Output
4/4
89Step 3: Output
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 | 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 | The evaluated outputs stayed inside the "Generate leave-one-out sensitivity analysis plots for meta-analysis. Input is a CSV file... 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 Capability79 / 100 — 8 Categories
Functional Suitability
Functional suitability was softened by the legacy issue 'Improve stress-case output rigor'. Stress and boundary scenarios show weaker consistency
10 / 12
83%
Reliability
Related legacy finding for meta-sensitivity-plot: Improve stress-case output rigor. Stress and boundary scenarios show weaker consistency
10 / 12
83%
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.
12 / 16
75%
Human Usability
The archived score suggests the output contract could be a little easier for users to inspect or reuse.
6 / 8
75%
Security
Security remained strong, though the archived review still left some room for clearer execution guardrails.
9 / 12
75%
Maintainability
The analysis package is maintainable overall, though the archived score suggests modest cleanup headroom.
9 / 12
75%
Agent-Specific
The archived deduction in agent specific traces back to: Improve stress-case output rigor. Stress and boundary scenarios show weaker consistency
15 / 20
75%
Core Capability Total79 / 100
Medical TaskExecution Average: 90.6 / 100 — Assertions: 20/20 Passed
95
Canonical
"Generate leave-one-out sensitivity analysis plots for meta-analysis. Input is a CSV file containing meta-analysis data; outputs are a sensitivity forest plot (PNG) and a sensitivity data table (CSV) showing pooled effect estimates after excluding each study in turn."
4/4 ✓
91
Variant A
"Generate leave-one-out sensitivity analysis plots for meta-analysis. Input is a CSV file containing meta-analysis data; outputs are a sensitivity forest plot (PNG) and a sensitivity data table (CSV) showing pooled effect estimates after excluding each study in turn."
4/4 ✓
89
Edge
Step 1: Validate input
4/4 ✓
89
Variant B
Step 3: Output
4/4 ✓
89
Stress
Step 3: Output
4/4 ✓
95
Canonical✅ Pass
"Generate leave-one-out sensitivity analysis plots for meta-analysis. Input is a CSV file containing meta-analysis data; outputs are a sensitivity forest plot (PNG) and a sensitivity data table (CSV) showing pooled effect estimates after excluding each study in turn."
"Generate leave-one-out sensitivity analysis plots for... remained tied to the documented analysis contract even when the preserved evidence centered on instructions instead of a full rerun.
Basic 35/40|Specialized 60/60|Total 95/100
✅A1The meta-sensitivity-plot 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
91
Variant A✅ Pass
"Generate leave-one-out sensitivity analysis plots for meta-analysis. Input is a CSV file containing meta-analysis data; outputs are a sensitivity forest plot (PNG) and a sensitivity data table (CSV) showing pooled effect estimates after excluding each study in turn."
The archived run treated "Generate leave-one-out sensitivity analysis plots for... as a bounded analysis workflow rather than a purely narrative instruction path.
Basic 33/40|Specialized 58/60|Total 91/100
✅A1The meta-sensitivity-plot 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
89
Edge✅ Pass
Step 1: Validate input
The archived run treated Step 1: Validate input as a bounded analysis workflow rather than a purely narrative instruction path.
Basic 32/40|Specialized 57/60|Total 89/100
✅A1The meta-sensitivity-plot 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
89
Variant B✅ Pass
Step 3: Output
The archived run treated Step 3: Output as a bounded analysis workflow rather than a purely narrative instruction path.
Basic 31/40|Specialized 58/60|Total 89/100
✅A1The meta-sensitivity-plot 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
89
Stress✅ Pass
Step 3: Output
The archived run treated Step 3: Output as a bounded analysis workflow rather than a purely narrative instruction path.
Basic 28/40|Specialized 60/60|Total 89/100
✅A1The meta-sensitivity-plot 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 Total90.6 / 100
Key Strengths
- Primary routing is Data Analysis with execution mode B
- Static quality score is 79/100 and dynamic average is 77.6/100
- Assertions and command execution outcomes are recorded per input for human review
- Execution verification summary: Script verification 1/1; adjustment=5. sensitivity_analysis.py: OK