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.
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
SkillHub CLI
skillhub install asif2bd/openclaw-skill-lazy-loaderInspect the source and compatibility requirements, then follow its installation steps.
Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.
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...
These signals come from indexed source analysis and may lag behind changes. Check the current source files.
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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