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VS-Enhanced Evidence Quality Appraiser - Prevents Mode Collapse with context-adaptive quality assessment Enhanced VS 3-Phase process: Avoids automatic tool application, delivers research-specific evaluation strategies Use when: appraising study quality, assessing risk of bias,

From plugin
auto-empirical-research-skills
5k200 skills

Claude Code

$ npx -y skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill b2 --agent claude-code

SKILL.md

b2.SKILL.md
name: b2
description: |
  VS-Enhanced Evidence Quality Appraiser - Prevents Mode Collapse with context-adaptive quality assessment
  Enhanced VS 3-Phase process: Avoids automatic tool application, delivers research-specific evaluation strategies
  Use when: appraising study quality, assessing risk of bias, grading evidence
  Triggers: quality appraisal, RoB, GRADE, Newcastle-Ottawa, risk of bias, methodological quality
version: "12.0.1"

⛔ Prerequisites (v8.2 — MCP Enforcement)

`diverga_check_prerequisites("b2")` → must return `approved: true` If not approved → AskUserQuestion for each missing checkpoint (see `.claude/references/checkpoint-templates.md`)

Checkpoints During Execution

  • 🟠 CP_QUALITY_REVIEW → `diverga_mark_checkpoint("CP_QUALITY_REVIEW", decision, rationale)`

Fallback (MCP unavailable)

Read `.research/decision-log.yaml` directly to verify prerequisites. Conversation history is last resort.

---

Evidence Quality Appraiser

**Agent ID**: 06 **Category**: B - Literature & Evidence **VS Level**: Enhanced (3-Phase) **Tier**: Core **Icon**: 🔬

Overview

Systematically evaluates methodological quality and risk of bias in individual studies. Selects and applies appropriate assessment tools based on study design type.

Applies **VS-Research methodology** to go beyond mechanical tool application, providing differentiated quality evaluation strategies tailored to research context and purpose.

VS-Research 3-Phase Process (Enhanced)

Phase 1: Modal Quality Assessment Approach Identification

**Purpose**: Recognize limitations of mechanical tool application

⚠️ **Modal Warning**: The following are the most predictable quality assessment approaches:

| Modal Approach | T-Score | Limitation |
|----------------|---------|------------|
| "RCT → Apply RoB 2.0" | 0.90 | Automatic matching ignoring context |
| "Observational → Apply NOS" | 0.88 | Ignores tool limitations |
| "Report GRADE rating only" | 0.85 | Rating rationale unclear |

➡️ Tool application is baseline. Proceeding with context-adaptive assessment.

Phase 2: Context-Adaptive Evaluation Strategy

**Purpose**: Present evaluation approaches suited to research purpose and context

**Direction A** (T ≈ 0.7): Standard tool + contextual interpretation
- Standard tool application + domain-specific weighting
- Suitable for: General systematic reviews

**Direction B** (T ≈ 0.4): Multi-tool triangulation
- Simultaneous application of multiple tools + discrepancy analysis
- Additional field-specific quality criteria
- Suitable for: Methodology papers, high-quality reviews

**Direction C** (T < 0.3): Purpose-specific evaluation
- Differentiated criteria by meta-analysis purpose
- Propose new evaluation dimensions (reproducibility, transparency)
- Suitable for: Methodological innovation, guideline development

Phase 4: Recommendation Execution

Based on **selected evaluation strategy**: 1. State tool selection rationale 2. Domain-specific detailed assessment + interpretive commentary 3. Meta-analysis utilization recommendations 4. Sensitivity analysis necessity determination

---

Quality Assessment Typicality Score Reference Table

T > 0.8 (Modal - Supplementation Required):
├── Study type → Standard tool automatic matching
├── Yes/No per checklist item
├── Report only total score or rating
└── Judgment rationale unclear

T 0.5-0.8 (Established - Add Interpretation):
├── Specific rationale per domain
├── Interpret meaning in research context
├── Meta-analysis inclusion/exclusion recommendation
└── Sensitivity analysis necessity determination

T 0.3-0.5 (In-depth - Recommended):
├── Multi-tool triangulation
├── Additional field-specific criteria
├── Quality-effect size relationship analysis
└── Rating uncertainty quantification

T < 0.3 (Innovative - For Leading Research):
├── Propose new evaluation dimensions
├── Critical discussion of tool limitations
├── Purpose-specific evaluation framework
└── Quality assessment uncertainty propagation

When to Use

  • Evaluating included studies in systematic reviews
  • Verifying study quality before meta-analysis
  • Assessing evidence for evidence-based decision making
  • Judging reliability of research findings

Core Functions

1. **Study Type-Specific Tool Selection**

  • RCT: Cochrane Risk of Bias 2.0
  • Observational studies: Newcastle-Ottawa Scale, ROBINS-I
  • Qualitative studies: CASP, JBI Critical Appraisal
  • Mixed methods: MMAT

2. **Risk of Bias Assessment**

  • Domain-specific bias evaluation
  • Overall risk of bias judgment
  • Evidence-based determination

3. **GRADE Certainty Rating**

  • Certainty of evidence assessment
  • Identify upgrade/downgrade factors
  • Support recommendation strength judgment

4. **Quality Summary Visualization**

  • Traffic light plot
  • Summary of findings table

Assessment Tool Library

RCT: Cochrane Risk of Bias 2.0

| Domain | Assessment Content | |--------|-------------------| | D1 | Bias arising from randomization process | | D2 | Bias due to deviations from intended interventions | | D3 | Bias due to missing outcome data | | D4 | Bias in measurement of outcome | | D5 | Bias in selection of reported result |

**Judgment**: Low risk / Some concerns / High risk

Observational Studies: Newcastle-Ottawa Scale

| Domain | Items | Points | |--------|-------|--------| | Selection | Representativeness of exposed cohort | ★ | | | Selection of non-exposed cohort | ★ | | | Ascertainment of exposure | ★ | | | Demonstration outcome not present at start | ★ | | Comparability | Comparability of cohorts | ★★ | | Outcome | Assessment of outcome | ★ | | | Adequate follow-up length | ★ | | | Adequacy of follow-up | ★ |

**Total Score**: /9 points

Qualitative Studies: CASP Checklist

1. Was there a clear statement of aims? 2. Is a qualitative methodology appropriate? 3. Was the research design appropriate? 4. Was the recruitment strategy appropriate? 5. W

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b2 installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.