Data Analysis
meta-forest-binary-plot
91100Total 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
100"Generate meta-analysis forest plots for binary classification data. Input is a CSV file containing study names, event counts and sample sizes for experimental and control groups. Output includes forest plot PNG and data table CSV."
4/4
96Step 2: Execute R Script (Priority)
4/4
94Step 1: Validate Input Data
4/4
94Step 3: Output Results
4/4
94Step 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 forest plots for binary classification data. Input is a CSV file... rather than overclaiming what the records supported. |
| 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 Capability83 / 100 — 8 Categories
Functional Suitability
Functional suitability stayed high, with only minor headroom in how the analysis outcome is framed.
11 / 12
92%
Reliability
The legacy audit preserved a modest reliability gap around harder runs or more demanding inputs.
10 / 12
83%
Performance & Context
Performance context reached full score in the archived evaluation.
8 / 8
100%
Agent Usability
The packaged analysis path is understandable, though the archived score suggests slightly clearer routing would help.
13 / 16
81%
Human Usability
Related legacy finding for meta-forest-binary-plot: Minor polish before wide rollout. No major defects found
7 / 8
88%
Security
The packaged workflow stayed safe overall, with only a small remaining deduction around boundary signaling.
9 / 12
75%
Maintainability
Maintainability stayed solid, with only limited room to simplify scripts, dependencies, or packaging structure.
9 / 12
75%
Agent-Specific
The archived review found good agent alignment here, while still leaving some room for more explicit orchestration cues.
16 / 20
80%
Core Capability Total83 / 100
Medical TaskExecution Average: 95.6 / 100 — Assertions: 20/20 Passed
100
Canonical
"Generate meta-analysis forest plots for binary classification data. Input is a CSV file containing study names, event counts and sample sizes for experimental and control groups. Output includes forest plot PNG and data table CSV."
4/4 ✓
96
Variant A
Step 2: Execute R Script (Priority)
4/4 ✓
94
Edge
Step 1: Validate Input Data
4/4 ✓
94
Variant B
Step 3: Output Results
4/4 ✓
94
Stress
Step 3: Output Results
4/4 ✓
100
Canonical✅ Pass
"Generate meta-analysis forest plots for binary classification data. Input is a CSV file containing study names, event counts and sample sizes for experimental and control groups. Output includes forest plot PNG and data table CSV."
The archived run for "Generate meta-analysis forest plots for binary classification... confirmed the helper entrypoint and left the workflow in a stable state.
Basic 38/40|Specialized 60/60|Total 100/100
✅A1The meta-forest-binary-plot output structure matches the documented deliverable
✅A2The script execution path completed successfully 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
96
Variant A✅ Pass
Step 2: Execute R Script (Priority)
The Step 2: Execute R Script (Priority) path verified the packaged helper command without exposing a deeper execution issue.
Basic 36/40|Specialized 60/60|Total 96/100
✅A1The meta-forest-binary-plot output structure matches the documented deliverable
✅A2The script execution path completed successfully 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
94
Edge✅ Pass
Step 1: Validate Input Data
The archived run for Step 1: Validate Input Data confirmed the helper entrypoint and left the workflow in a stable state.
Basic 35/40|Specialized 59/60|Total 94/100
✅A1The meta-forest-binary-plot output structure matches the documented deliverable
✅A2The script execution path completed successfully 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
94
Variant B✅ Pass
Step 3: Output Results
For Step 3: Output Results, the preserved evidence is lightweight but positive: the packaged validation command behaved as expected.
Basic 34/40|Specialized 60/60|Total 94/100
✅A1The meta-forest-binary-plot output structure matches the documented deliverable
✅A2The script execution path completed successfully 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
94
Stress✅ Pass
Step 3: Output Results
The archived run for Step 3: Output Results confirmed the helper entrypoint and left the workflow in a stable state.
Basic 31/40|Specialized 60/60|Total 94/100
✅A1The meta-forest-binary-plot output structure matches the documented deliverable
✅A2The script execution path completed successfully 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 Total95.6 / 100
Key Strengths
- Primary routing is Data Analysis with execution mode B
- Static quality score is 83/100 and dynamic average is 82.6/100
- Assertions and command execution outcomes are recorded per input for human review
- Execution verification summary: Script verification 3/3; adjustment=5. extract_criteria.py: OK; forest_binary.py: OK; validate_skill.py: OK