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 · 526 · 0 current installs · 0 all-time installs
⭐ 0
安装量（当前） 0
🛡 VirusTotal ：良性 · OpenClaw ：良性
Package：1kalin/afrexai-capacity-planner
安全扫描（ClawHub）
- VirusTotal ：良性
- OpenClaw ：良性
OpenClaw 评估
Instruction-only capacity-planning skill that is internally consistent with its stated purpose and does not request credentials, installs, or perform out-of-scope actions.
目的
The README and SKILL.md both describe a capacity-planning assistant (team/infrastructure modeling, scenario analysis, recommendations). There are no declared binaries, environment variables, or config paths that are unrelated to that purpose. The only minor issue is that the top-level description field is empty in the registry metadata, but the included files provide the expected functionality.
说明范围
All runtime instructions are high-level workflow guidance (what to ask, what outputs to produce). The SKILL.md does not instruct the agent to read local files, access environment variables, call arbitrary endpoints, or exfiltrate data. Output format and scenario templates are scoped to capacity planning.
安装机制
This is an instruction-only skill with no install spec and no code files — nothing is written to disk or downloaded. That is the lowest-risk install model.
证书
The skill declares no required environment variables, credentials, or config paths. There are no requests for keys, tokens, or unrelated service credentials — proportional to the described purpose.
持久
Flags show default behavior (always: false, agent-invocable, model invocation allowed). The skill does not request permanent presence nor instruct modifications to other skills or system-wide settings.
综合结论
This skill appears coherent and low-risk: it only provides instructions for capacity planning and requests no credentials or installs. Before installing, consider: (1) what team/project data you'll share with the agent—avoid pasting secrets or sensitive PII; (2) the external links in the docs are marketing pages—verify them independently before paying; and (3) if you prefer to limit autonomous behavior, restrict model-invocation or agent permi…
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「Capacity Planner」。简介：Analyzes team size, workload, and pipeline data to forecast capacity, identify …。
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-capacity-planner/SKILL.md
（来源：yingzhi8.cn 技能库）SKILL.md
# Capacity Planner
Plan team and infrastructure capacity before it becomes a crisis.
## What It Does
Takes your current workload data — team size, utilization rates, project pipeline, seasonal patterns — and builds a forward-looking capacity model. Flags bottlenecks 4-8 weeks before they hit.
## When to Use
- Sprint planning feels like guesswork
- You're not sure if you can take on a new client/project
- Hiring decisions need data, not gut feel
- Infrastructure keeps getting slammed at predictable times
## How to Use
Tell the agent about your situation:
```
"We have 8 engineers, 3 active projects, and a new client starting in March. Can we handle it?"
```
The agent will:
1. **Audit current load** — Map people to commitments, calculate true utilization (not the number in your head)
2. **Model scenarios** — What happens if the new project lands? What if two people quit? What if scope grows 30%?
3. **Flag risks** — Identify single points of failure, overloaded roles, deadline clusters
4. **Recommend actions** — Hire, redistribute, defer, or say no — with numbers behind each option
## Capacity Framework
### Utilization Bands
| Band | Rate | Meaning |
|------|------|---------|
| 🟢 Green | <70% | Healthy buffer for unplanned work |
| 🟡 Yellow | 70-85% | Sustainable but tight |
| 🔴 Red | >85% | Burnout zone — something will slip |
### Key Metrics
- **Effective capacity** = headcount × available hours × efficiency factor (typically 0.7-0.8)
- **Demand pipeline** = committed hours + probable hours (weighted by likelihood)
- **Buffer ratio** = (capacity - demand) / capacity — target 15-25%
- **Time to constraint** = weeks until demand exceeds capacity at current trajectory
### Scenario Template
For each scenario, output:
- Headcount needed vs. available
- Skill gaps (specific roles/capabilities missing)
- Timeline risk (which deadlines move)
- Cost impact (overtime, contractors, lost revenue from saying no)
- Recommended action with confidence level
## Output Format
```
CAPACITY SNAPSHOT — [Date]
━━━━━━━━━━━━━━━━━━━━━━━━━━
Team: [size] | Utilization: [%] | Buffer: [%]
Status: 🟢/🟡/🔴
CURRENT COMMITMENTS
- [Project A]: [X people, Y hours/week, end date]
- [Project B]: ...
PIPELINE (next 8 weeks)
- [Incoming work]: probability %, estimated load
- ...
RISKS
1. [Risk description + impact + timeframe]
2. ...
SCENARIOS
A) [Scenario]: [outcome summary]
B) [Scenario]: [outcome summary]
RECOMMENDATION
[Clear action with reasoning]
```
## Tips
- Refresh capacity snapshots weekly during planning
- Track actual vs. predicted utilization to calibrate your efficiency factor
- Include non-project work (meetings, support, admin) — it's usually 20-30% of capacity
- Don't plan above 80% utilization. The remaining 20% isn't slack, it's where real work happens.
## Go Deeper
Your capacity model is one piece of operational planning. For full business context packs covering finance, operations, and growth strategy across 10 industries:
→ **[AfrexAI Context Packs](https://afrexai-cto.github.io/context-packs/)** — $47 each, built by operators who've done the work.
→ **[AI Revenue Calculator](https://afrexai-cto.github.io/ai-revenue-calculator/)** — Find out where your business is leaking money (free tool).
→ **[Agent Setup Wizard](https://afrexai-cto.github.io/agent-setup/)** — Get your AI agent configured for your specific business in 5 minutes.