bias-assessor
Add bias/risk-of-bias assessment fields to an extraction table and populate them consistently. **Trigger**: bias, risk-of-bias, RoB, evidence quality, 偏倚评估, 证据质量. **Use when**: systematic review 已生成 `papers/extraction_table.csv`，需要在 synthesis 前补齐偏倚/质量字段。 **Skip if**: 不是 systematic review，或还没有 `papers/extraction_table.csv`。 **Network**: none. **Guardrail**: 使用简单可复核刻度（low/unclear/high）+ 简短 notes；保持字段一致性。
Packaged view
This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Install command
npx @skill-hub/cli install willoscar-research-units-pipeline-skills-bias-assessor
Repository
Skill path: .codex/skills/bias-assessor
Add bias/risk-of-bias assessment fields to an extraction table and populate them consistently. **Trigger**: bias, risk-of-bias, RoB, evidence quality, 偏倚评估, 证据质量. **Use when**: systematic review 已生成 `papers/extraction_table.csv`，需要在 synthesis 前补齐偏倚/质量字段。 **Skip if**: 不是 systematic review，或还没有 `papers/extraction_table.csv`。 **Network**: none. **Guardrail**: 使用简单可复核刻度（low/unclear/high）+ 简短 notes；保持字段一致性。
Open repositoryBest for
Primary workflow: Ship Full Stack.
Technical facets: Full Stack.
Target audience: everyone.
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: WILLOSCAR.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install bias-assessor into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/WILLOSCAR/research-units-pipeline-skills before adding bias-assessor to shared team environments
- Use bias-assessor for development workflows
Works across
Favorites: 0.
Sub-skills: 0.
Aggregator: No.
Original source / Raw SKILL.md
--- name: bias-assessor description: | Add bias/risk-of-bias assessment fields to an extraction table and populate them consistently. **Trigger**: bias, risk-of-bias, RoB, evidence quality, 偏倚评估, 证据质量. **Use when**: systematic review 已生成 `papers/extraction_table.csv`，需要在 synthesis 前补齐偏倚/质量字段。 **Skip if**: 不是 systematic review，或还没有 `papers/extraction_table.csv`。 **Network**: none. **Guardrail**: 使用简单可复核刻度（low/unclear/high）+ 简短 notes；保持字段一致性。 --- # Bias Assessor (risk-of-bias, lightweight) Goal: make evidence quality explicit in a way that is quick, consistent, and auditable. ## Inputs - `papers/extraction_table.csv` ## Outputs - Updated `papers/extraction_table.csv` ## Recommended fields Use a simple 3-level scale (all lowercase): `low | unclear | high`. Suggested columns to add (if missing): - `rob_selection` - `rob_measurement` - `rob_confounding` - `rob_reporting` - `rob_overall` - `rob_notes` ## Workflow 1. Read `papers/extraction_table.csv` and identify the set of included studies. 2. If RoB columns are missing, add them (keep names stable once introduced). 3. For each study, fill each RoB domain: - `low`: design/reporting plausibly controls the bias - `unclear`: not enough information to judge - `high`: clear risk (e.g., missing controls, ambiguous measurement, selective reporting) 4. Set `rob_overall` conservatively: - `high` if any domain is `high` - `unclear` if no `high` but at least one `unclear` - `low` only if all domains are `low` 5. Add 1–3 short notes in `rob_notes` that justify the rating. ## Definition of Done - [ ] Every included paper row has all RoB columns filled. - [ ] Values are strictly from `low|unclear|high` (no free-form scale drift). - [ ] Notes are short and specific (what was missing / what was strong). ## Troubleshooting ### Issue: the table has mixed or inconsistent RoB column names **Fix**: - Normalize to the recommended column names and keep a single set across all rows. ### Issue: the paper lacks enough methodological detail **Fix**: - Prefer `unclear` with a concrete note (“no details on X”) rather than guessing.