Data Analysis
meta-funnel-plot
85100Total Score
Core Capability
83 / 100
Functional Suitability
11 / 12
Reliability
10 / 12
Performance & Context
8 / 8
Agent Usability
13 / 16
Human Usability
7 / 8
Security
9 / 12
Maintainability
9 / 12
Agent-Specific
16 / 20
Medical Task
20 / 20 Passed
91"Generate Meta-analysis funnel plots and perform publication bias testing. Takes CSV file with Meta-analysis data as input, outputs funnel plot PNG, Egger test and Begg test results."
4/4
87Step 2: Execute R Script
4/4
85Step 1: Validate Input Data
4/4
85Step 3: Output Results
4/4
85Step 3: Output Results
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 | 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 | Practice boundaries held because the package remained focused on "Generate Meta-analysis funnel plots and perform publication bias testing. Takes CSV file... rather than overclaiming what the records supported. |
| Methodological Ground | PASS | The archived review found the package methodologically anchored to a named assessment rule set. |
| Code Usability | PASS | No code-usability failure was preserved for meta-funnel-plot in the legacy evaluation. |
Core Capability83 / 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
Reliability was softened by the legacy issue 'Improve stress-case output rigor'. Stress and boundary scenarios show weaker consistency
10 / 12
83%
Performance & Context
Performance context reached full score in the archived evaluation.
8 / 8
100%
Agent Usability
Agent usability was strong, but the workflow could surface its entry conditions a little more directly.
13 / 16
81%
Human Usability
The archived score suggests the output contract could be a little easier for users to inspect or reuse.
7 / 8
88%
Security
A modest security gap remained in the archived evaluation despite otherwise controlled workflow behavior.
9 / 12
75%
Maintainability
Maintainability stayed solid, with only limited room to simplify scripts, dependencies, or packaging structure.
9 / 12
75%
Agent-Specific
Agent specific was softened by the legacy issue 'Improve stress-case output rigor'. Stress and boundary scenarios show weaker consistency
16 / 20
80%
Core Capability Total83 / 100
Medical TaskExecution Average: 86.6 / 100 — Assertions: 20/20 Passed
91
Canonical
"Generate Meta-analysis funnel plots and perform publication bias testing. Takes CSV file with Meta-analysis data as input, outputs funnel plot PNG, Egger test and Begg test results."
4/4 ✓
87
Variant A
Step 2: Execute R Script
4/4 ✓
85
Edge
Step 1: Validate Input Data
4/4 ✓
85
Variant B
Step 3: Output Results
4/4 ✓
85
Stress
Step 3: Output Results
4/4 ✓
91
Canonical✅ Pass
"Generate Meta-analysis funnel plots and perform publication bias testing. Takes CSV file with Meta-analysis data as input, outputs funnel plot PNG, Egger test and Begg test results."
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 meta-funnel-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
87
Variant A✅ Pass
Step 2: Execute R Script
The archived run treated Step 2: Execute R Script as a bounded analysis workflow rather than a purely narrative instruction path.
Basic 34/40|Specialized 53/60|Total 87/100
✅A1The meta-funnel-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
85
Edge✅ Pass
Step 1: Validate Input Data
The archived run treated Step 1: Validate Input Data as a bounded analysis workflow rather than a purely narrative instruction path.
Basic 33/40|Specialized 52/60|Total 85/100
✅A1The meta-funnel-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
85
Variant B✅ Pass
Step 3: Output Results
This variant b case stayed within the packaged analysis boundary and kept a reviewable task contract.
Basic 32/40|Specialized 53/60|Total 85/100
✅A1The meta-funnel-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
85
Stress✅ Pass
Step 3: Output Results
The archived run treated Step 3: Output Results as a bounded analysis workflow rather than a purely narrative instruction path.
Basic 29/40|Specialized 56/60|Total 85/100
✅A1The meta-funnel-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 Total86.6 / 100
Key Strengths
- Primary routing is Data Analysis with execution mode B
- Static quality score is 83/100 and dynamic average is 78.6/100
- Assertions and command execution outcomes are recorded per input for human review
- Execution verification summary: Script verification 0/2; adjustment=0. funnel_plot.py: rc=1; run_funnel_plot.py: rc=1