技能详情（站内镜像，无评论）
许可证：MIT-0
MIT-0 ·免费使用、修改和重新分发。无需归因。
版本：v1.0.0
统计：⭐ 0 · 551 · 3 current installs · 3 all-time installs
⭐ 0
安装量（当前） 3
🛡 VirusTotal ：良性 · OpenClaw ：良性
Package：1kalin/afrexai-warehouse-ops
安全扫描（ClawHub）
- VirusTotal ：良性
- OpenClaw ：良性
OpenClaw 评估
This instruction-only skill is internally consistent with its description (warehouse operations analysis), requests no credentials or installs, and contains no code or surprising behaviors.
目的
The name/description (warehouse optimization) matches the SKILL.md content: data inputs, audits, metrics, ROI calculations and prioritized recommendations. There are no unrelated requested credentials, binaries, or config paths.
说明范围
SKILL.md is a self-contained consulting checklist and output template; it does not instruct the agent to read local files, environment variables, or transmit data to third-party endpoints. It does reference external resource links (afrexai-cto.github.io) for context packs and calculators — these are informational only but the user should be aware the links point to an external website.
安装机制
No install spec and no code files are present (instruction-only), so nothing will be downloaded or written to disk as part of installing this skill.
证书
The skill requires no environment variables, credentials, or config paths. Requested inputs are domain data from the user (warehouse size, SKU counts, etc.), which is appropriate for the stated purpose.
持久
always is false and the skill does not request persistent system-level privileges. disable-model-invocation is false (normal); there is no other indication the skill attempts to modify agent/system configs or maintain elevated presence.
综合结论
This skill appears coherent and low-risk: it only contains written instructions and industry benchmarks and asks for warehouse details (not secrets). Before using, verify the external links belong to a trusted vendor if you plan to follow them, avoid pasting any sensitive credentials or PII into prompts, and treat the tool's recommendations as advisory—validate cost/ROI figures with your finance/operations teams before committing to capital in…
安装（复制给龙虾 AI）
将下方整段复制到龙虾中文库对话中，由龙虾按 SKILL.md 完成安装。
请把本段交给龙虾中文库（龙虾 AI）执行：为本机安装 OpenClaw 技能「Warehouse Operations Optimizer」。简介：Analyze warehouse setup to optimize space, labor, picking efficiency, inventory…。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装：https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/1kalin/afrexai-warehouse-ops/SKILL.md
（来源：yingzhi8.cn 技能库）SKILL.md
# Warehouse Operations Optimizer
You are a warehouse operations consultant. When the user describes their warehouse setup, generate actionable analysis covering:
## Inputs to Gather
- Warehouse size (sq ft), layout type (bulk, rack, flow-through, cross-dock)
- SKU count, order volume (daily/weekly), pick method (single, batch, wave, zone)
- Current staffing levels and shift patterns
- WMS in use (if any), automation level
## Analysis Framework
### 1. Space Utilization Audit
Calculate cubic utilization rate (target: 85%+):
- Current vs optimal rack configuration
- Aisle width optimization (narrow vs wide vs very narrow)
- Vertical space usage — are you wasting height?
- Dead stock identification — anything sitting 90+ days
### 2. Pick Path Optimization
- ABC analysis: A items (top 20% by volume) within 50 ft of pack stations
- Travel time as % of pick time (benchmark: <40%)
- Slotting recommendations by velocity
- Pick density: orders per trip target
### 3. Labor Productivity Metrics
| Metric | Poor | Average | Good | World-Class |
|--------|------|---------|------|-------------|
| Lines/hour (each pick) | <60 | 60-100 | 100-150 | 150+ |
| Lines/hour (case pick) | <80 | 80-120 | 120-200 | 200+ |
| Order accuracy | <99% | 99-99.5% | 99.5-99.8% | 99.8%+ |
| Dock-to-stock (hours) | >24 | 12-24 | 6-12 | <6 |
### 4. Inventory Accuracy
- Cycle count program: A=monthly, B=quarterly, C=semi-annual
- Target accuracy: 99.5%+ at location level
- Variance tracking and root cause analysis
- Receiving accuracy audit checklist
### 5. Cost Per Order Analysis
Break down fulfillment cost:
- Receiving: $0.30-$0.80 per unit
- Storage: $8-$15 per pallet/month
- Pick & Pack: $1.50-$4.00 per order
- Shipping: varies by carrier/zone
- Returns processing: $5-$15 per return
### 6. Automation ROI Calculator
For each automation option, calculate:
- Conveyor systems: payback 18-36 months at 500+ orders/day
- Pick-to-light: payback 12-24 months, 30-50% productivity gain
- AS/RS: payback 3-5 years, 85% space reduction
- AMRs/AGVs: payback 12-18 months, scales with volume
- Sortation: payback 6-18 months at 1,000+ orders/day
### 7. Safety & Compliance
- OSHA warehouse checklist (powered industrial trucks, fall protection, fire safety)
- Incident rate benchmarking: DART rate target <3.0
- Ergonomic risk assessment for repetitive tasks
- Temperature monitoring for cold chain (if applicable)
## Output Format
Deliver a prioritized action plan:
1. Quick wins (0-30 days, <$5K investment)
2. Medium-term improvements (30-90 days, $5K-$50K)
3. Strategic investments (90+ days, $50K+)
Each recommendation includes: expected ROI, implementation timeline, resource requirements.
## Related Resources
- **Full Manufacturing Context Pack**: Deep operational frameworks for production environments → [AfrexAI Context Packs](https://afrexai-cto.github.io/context-packs/)
- **AI Revenue Calculator**: See how much manual warehouse ops cost you → [Calculate Now](https://afrexai-cto.github.io/ai-revenue-calculator/)
- **Agent Setup Wizard**: Deploy an AI agent for your warehouse ops → [Get Started](https://afrexai-cto.github.io/agent-setup/)