agent-pack-n-go
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Dramatically reduce per-session token usage by loading skills and context files only when needed — not at session start. Includes the SKILLS catalog pattern, AGENTS.md lazy loading strategy, and a Python helper that recommends exactly which files to load for any given task. Compatible with all OpenClaw agents. Works alongside Token Optimizer.
请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。
SkillHub CLI
skillhub install asif2bd/openclaw-skill-lazy-loader打开来源仓库,查看说明和兼容环境后,按来源提供的命令或步骤安装。
将来源链接提供给你的 Agent,让它先读取说明、核对依赖,并向你说明将执行的安装步骤。
Stop loading every skill file at session start. Load what you need, when you need it — and cut your token usage by 40–70%.
Most OpenClaw agents load their entire skill library at startup:
# AGENTS.md (naive approach)
Read ALL of these before starting:
- skills/python/SKILL.md
- skills/git/SKILL.md
- skills/docker/SKILL.md
- skills/aws/SKILL.md
- skills/browser/SKILL.md
... (20 more)
Each session burns 3,000–15,000 tokens just loading context that may never be used. At scale, this is your biggest cost.
Instead of loading skills upfront, agents check a SKILLS catalog (a lightweight index) and load individual skill files only when a task requires them.
Before: Load 20 skill files = ~12,000 tokens/session After: Load catalog (300 tokens) + 1–2 relevant skills (~800 tokens) = ~1,100 tokens/session
That's an 89% reduction on context loading alone.
Create SKILLS.md in your agent workspace — a lightweight index of all available skills:
# Available Skills
| Skill | File | Use When |
|-------|------|----------|
| Python | skills/python/SKILL.md | Writing/debugging Python code |
| Git | skills/git/SKILL.md | Git operations, PRs, branches |
| Docker | skills/docker/SKILL.md | Containers, images, compose |
| Browser | skills/browser/SKILL.md | Web scraping, UI automation |
| AWS | skills/aws/SKILL.md | Cloud deployments, S3, Lambda |
This catalog is the ONLY file loaded at session start. ~200–400 tokens instead of 10,000+.
See SKILLS.md.template for a complete starter template.
Replace bulk loading with the catalog pattern:
## Skills
At session start: Read SKILLS.md (the index only).
When a task needs a skill: Read the specific SKILL.md for that skill.
Never load all skills upfront.
### Loading Decision
Before load...
这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。
Stop loading every skill file at session start. Cut context loading costs by 40–93%.
Most OpenClaw agents eagerly load all their skill files at session start — burning thousands of tokens on context that may never be used. This skill teaches you (and your agents) how to fix that.
The pattern: Use a lightweight SKILLS catalog (~300 tokens) at startup. Load individual skill files only when a task actually needs them.
Result: 40–93% reduction in context loading costs, depending on your skill library size.
clawhub install openclaw-skill-lazy-loader
# 1. Copy the SKILLS catalog template to your agent workspace
cp ~/.openclaw/skills/openclaw-skill-lazy-loader/SKILLS.md.template ~/my-agent/SKILLS.md
# 2. Edit it — fill in your actual skills
nano ~/my-agent/SKILLS.md
# 3. Update your AGENTS.md to use the lazy loading pattern
# (copy the relevant section from AGENTS.md.template)
# 4. Test the optimizer
python3 ~/.openclaw/skills/openclaw-skill-lazy-loader/context_optimizer.py recommend "your task"
| Skills in library | Before | After | Savings |
|---|---|---|---|
| 5 skills | ~3,000 tok | ~600 tok | 80% |
| 10 skills | ~6,500 tok | ~750 tok | 88% |
| 20 skills | ~13,000 tok | ~900 tok | 93% |
SKILL.md — Full implementation guideSKILLS.md.template — Ready-to-use skill catalog starterAGENTS.md.template — AGENTS.md lazy loading section to paste incontext_optimizer.py — CLI tool: recommends which skills to load per task→ [O...
# OpenClaw Skill Lazy Loader Stop loading every skill file at session start. Load what you need, when you need it — and cut your token usage by 40–70%. ## The Problem Most OpenClaw agents load their entire skill library at startup: ```markdown # AGENTS.md (naive approach) Read ALL of these before starting: - skills/python/SKILL.md - skills/git/SKILL.md - skills/docker/SKILL.md - skills/aws/SKILL.md - skills/browser/SKILL.md ... (20 more) ``` Each session burns **3,000–15,000 tokens** just loading context that may never be used. At scale, this is your biggest cost. ## The Solution: Lazy Loading Instead of loading skills upfront, agents check a **SKILLS catalog** (a lightweight index) and load individual skill files only when a task requires them. **Before:** Load 20 skill files = ~12,000 tokens/session **After:** Load catalog (300 tokens) + 1–2 relevant skills (~800 tokens) = **~1,100 tokens/session** That's an **89% reduction** on context loading alone. --- ## Implementation Guide ### Step 1: Create Your SKILLS Catalog Create `SKILLS.md` in your agent workspace — a lightweight index of all available skills: ```markdown # Available Skills | Skill | File | Use When | |-------|------|----------| | Python | skills/python/SKILL.md | Writing/debugging Python code | | Git | skills/git/SKILL.md | Git operations, PRs, branches | | Docker | skills/docker/SKILL.md | Containers, images, compose | | Browser | skills/browser/SKILL.md | Web scraping, UI automation | | AWS | skills/aws/SKILL.md | Cloud deployments, S3, Lambda | ``` This catalog is the ONLY file loaded at session start. ~200–400 tokens instead of 10,000+. See `SKILLS.md.template` for a complete starter template. ### Step 2: Update Your AGENTS.md Replace bulk loading with the catalog pattern: ```markdown ## Skills At session start: Read SKILLS.md (the index only). When a task needs a skill: Read the specific SKILL.md for that skill. Never load all skills upfront. ### Loading Decision Before load...
# OpenClaw Skill Lazy Loader > Stop loading every skill file at session start. Cut context loading costs by 40–93%. [](https://clawhub.ai/Asif2BD/openclaw-skill-lazy-loader) [](LICENSE) [](CHANGELOG.md) ## What It Does Most OpenClaw agents eagerly load all their skill files at session start — burning thousands of tokens on context that may never be used. This skill teaches you (and your agents) how to fix that. **The pattern:** Use a lightweight SKILLS catalog (~300 tokens) at startup. Load individual skill files only when a task actually needs them. **Result:** 40–93% reduction in context loading costs, depending on your skill library size. ## Install ```bash clawhub install openclaw-skill-lazy-loader ``` ## Quick Start ```bash # 1. Copy the SKILLS catalog template to your agent workspace cp ~/.openclaw/skills/openclaw-skill-lazy-loader/SKILLS.md.template ~/my-agent/SKILLS.md # 2. Edit it — fill in your actual skills nano ~/my-agent/SKILLS.md # 3. Update your AGENTS.md to use the lazy loading pattern # (copy the relevant section from AGENTS.md.template) # 4. Test the optimizer python3 ~/.openclaw/skills/openclaw-skill-lazy-loader/context_optimizer.py recommend "your task" ``` ## Token Savings | Skills in library | Before | After | Savings | |-------------------|--------|-------|---------| | 5 skills | ~3,000 tok | ~600 tok | **80%** | | 10 skills | ~6,500 tok | ~750 tok | **88%** | | 20 skills | ~13,000 tok | ~900 tok | **93%** | ## What's Included - **`SKILL.md`** — Full implementation guide - **`SKILLS.md.template`** — Ready-to-use skill catalog starter - **`AGENTS.md.template`** — AGENTS.md lazy loading section to paste in - **`context_optimizer.py`** — CLI tool: recommends which skills to load per task ## Pairs With → [O...
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