Protocol Design

faers-pharmacovigilance-disproportionality

Generates complete FAERS-style pharmacovigilance disproportionality research designs from a user-provided drug class, comparator strategy, adverse-event domain, and patient-group stratification. Always use this skill whenever a user wants to design, plan, or build a spontaneous-r

89100Total Score
Core Capability
92 / 100
Functional Suitability
12 / 12
Reliability
10 / 12
Performance & Context
7 / 8
Agent Usability
15 / 16
Human Usability
7 / 8
Security
12 / 12
Maintainability
11 / 12
Agent-Specific
18 / 20
Medical Task
34 / 35 Passed
91Canonical input for faers-pharmacovigilance-disproportionality
5/5
91Variant A input for faers-pharmacovigilance-disproportionality
5/5
88Variant B input for faers-pharmacovigilance-disproportionality
5/5
86Edge input for faers-pharmacovigilance-disproportionality
5/5
86Stress input for faers-pharmacovigilance-disproportionality
5/5
86Scope Boundary input for faers-pharmacovigilance-disproportionality
5/5
86Adversarial input for faers-pharmacovigilance-disproportionality
4/5

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 IntegrityPASSNo fabricated references, DOIs, PMIDs, statistical values, or clinical data detected.
Practice BoundariesPASSNo diagnostic conclusions or unapproved treatment recommendations produced.
Methodological GroundPASSNo methodological fallacies detected; ethical compliance requirements noted where applicable.
Code UsabilityN/ANo executable code generated; analysis pipeline planning only

Core Capability92 / 1008 Categories

Functional Suitability
Full marks (12/12); no significant issues detected.
12 / 12
100%
Reliability
Dataset Disclaimer present; four workload configs well-defined; minor gaps in parameter specification
10 / 12
83%
Performance & Context
Strong score (7/8); minor gaps noted.
7 / 8
88%
Agent Usability
Strong score (15/16); minor gaps noted.
15 / 16
94%
Human Usability
Strong score (7/8); minor gaps noted.
7 / 8
88%
Security
Full marks (12/12); no significant issues detected.
12 / 12
100%
Maintainability
Strong score (11/12); minor gaps noted.
11 / 12
92%
Agent-Specific
Concomitant drug exclusion logic is a critical safeguard against confounded safety signals
18 / 20
90%
Core Capability Total92 / 100

Medical TaskExecution Average: 87.7 / 100 — Assertions: 34/35 Passed

91
Canonical
Canonical input for faers-pharmacovigilance-disproportionality
5/5
91
Variant A
Variant A input for faers-pharmacovigilance-disproportionality
5/5
88
Variant B
Variant B input for faers-pharmacovigilance-disproportionality
5/5
86
Edge
Edge input for faers-pharmacovigilance-disproportionality
5/5
86
Stress
Stress input for faers-pharmacovigilance-disproportionality
5/5
86
Scope Boundary
Scope Boundary input for faers-pharmacovigilance-disproportionality
5/5
86
Adversarial
Adversarial input for faers-pharmacovigilance-disproportionality
4/5
91
Canonical✅ Pass
Canonical input for faers-pharmacovigilance-disproportionality

5/5 assertions passed.

Basic 36/40|Specialized 55/60|Total 91/100
A1Core assertion 1 for canonical input
A2Core assertion 2 for canonical input
A3Core assertion 3 for canonical input
A4Core assertion 4 for canonical input
A5Core assertion 5 for canonical input
Pass rate: 5 / 5
91
Variant A✅ Pass
Variant A input for faers-pharmacovigilance-disproportionality

5/5 assertions passed.

Basic 36/40|Specialized 55/60|Total 91/100
A1Core assertion 1 for variant a input
A2Core assertion 2 for variant a input
A3Core assertion 3 for variant a input
A4Core assertion 4 for variant a input
A5Core assertion 5 for variant a input
Pass rate: 5 / 5
88
Variant B✅ Pass
Variant B input for faers-pharmacovigilance-disproportionality

5/5 assertions passed.

Basic 35/40|Specialized 53/60|Total 88/100
A1Core assertion 1 for variant b input
A2Core assertion 2 for variant b input
A3Core assertion 3 for variant b input
A4Core assertion 4 for variant b input
A5Core assertion 5 for variant b input
Pass rate: 5 / 5
86
Edge✅ Pass
Edge input for faers-pharmacovigilance-disproportionality

5/5 assertions passed.

Basic 34/40|Specialized 52/60|Total 86/100
A1Core assertion 1 for edge input
A2Core assertion 2 for edge input
A3Core assertion 3 for edge input
A4Core assertion 4 for edge input
A5Core assertion 5 for edge input
Pass rate: 5 / 5
86
Stress✅ Pass
Stress input for faers-pharmacovigilance-disproportionality

5/5 assertions passed.

Basic 34/40|Specialized 52/60|Total 86/100
A1Core assertion 1 for stress input
A2Core assertion 2 for stress input
A3Core assertion 3 for stress input
A4Core assertion 4 for stress input
A5Core assertion 5 for stress input
Pass rate: 5 / 5
86
Scope Boundary✅ Pass
Scope Boundary input for faers-pharmacovigilance-disproportionality

5/5 assertions passed.

Basic 34/40|Specialized 52/60|Total 86/100
A1Core assertion 1 for scope boundary input
A2Core assertion 2 for scope boundary input
A3Core assertion 3 for scope boundary input
A4Core assertion 4 for scope boundary input
A5Core assertion 5 for scope boundary input
Pass rate: 5 / 5
86
Adversarial✅ Pass
Adversarial input for faers-pharmacovigilance-disproportionality

4/5 assertions passed.

Basic 34/40|Specialized 52/60|Total 86/100
A1Core assertion 1 for adversarial input
A2Core assertion 2 for adversarial input
A3Core assertion 3 for adversarial input
A4Core assertion 4 for adversarial input
A5Core assertion 5 for adversarial input
Pass rate: 4 / 5
Medical Task Total87.7 / 100

Key Strengths

  • Five study patterns provide comprehensive coverage of faers disproportionality with meddra-based ae extraction and comparator benchmarking research scenarios
  • Four workload configurations (Lite/Standard/Advanced/Publication+) with recommended primary plan enable broad applicability
  • Mandatory Dataset Disclaimer before all dataset-mentioning workflow sections prevents false resource claims
  • Strictly verified literature retrieval with no fabricated references maintains scientific integrity