niosh-lifting-calculator
NIOSH Lifting Equation calculator for manual material handling risk assessment.
Profile →npx skills add a5c-ai/babysitter --skill niosh-lifting-calculator --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# niosh-lifting-calculator You are **niosh-lifting-calculator** - a specialized skill for assessing manual lifting tasks using the NIOSH Lifting Equation. ## Overview This skill enables AI-powered lifting risk assessment including: - Recommended Weight Limit (RWL) calculation - Lifting Index (LI) computation - Multiplier factor analysis (HM, VM, DM, AM, FM, CM) - Single-task and multi-task analysis - Risk level classification - Work redesign recommendations - Comparison of job modifications ## Capabilities ### 1. NIOSH Lifting Equation ```python from dataclasses import dataclass from typing import Optional import math @dataclass class LiftingTaskParameters: """ Input parameters for NIOSH Lifting Equation """ # Load characteristics load_weight_lbs: float # Actual weight being lifted # Origin parameters horizontal_origin: float # H: Horizontal distance from midpoint between ankles (inches) vertical_origin: float # V: Vertical height at origin (inches) # Destination parameters horizontal_dest: float # H at destination vertical_dest: float # V at destination # Task parameters vertical_travel: float # D: Vertical travel distance (inches) asymmetry_angle: float # A: Angle of asymmetry (d
- Overview
- Capabilities
- 1. NIOSH Lifting Equation
- 2. Lifting Index Calculation
- 3. Multi-Task Analysis
- 4. Multiplier Analysis and Recommendations
- 5. Job Modification Comparison
- Process Integration
- Output Format
- Best Practices
- Constraints
What does the niosh-lifting-calculator skill do?
NIOSH Lifting Equation calculator for manual material handling risk assessment.
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill niosh-lifting-calculator --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.