- name
- openclaw-skill-lazy-loader
- description
- 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.
- version
- 1.0.0
- homepage
- https://github.com/Asif2BD/openclaw-skill-lazy-loader
- source
- https://github.com/Asif2BD/openclaw-skill-lazy-loader
- author
- Asif2BD
- license
- Apache 2.0
- security
- verified
- true
- auditor
- Oracle (Matrix Zion)
- audit_date
- 2026-02-28
- scripts_no_network
- true
- scripts_no_code_execution
- true
- scripts_no_subprocess
- true
- scripts_data_local_only
- true
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:
# 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:
# 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:
## 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 loading any skill file:
1. Does the current task need it? (yes → load it, no → skip)
2. Has it already been loaded this session? (yes → skip, no → load once)See AGENTS.md.template for the full recommended AGENTS.md skills section.
Step 3: Use the Context Optimizer (Optional)
The included context_optimizer.py analyzes your task description and recommends which skills to load:
python3 context_optimizer.py recommend "Write a Python script to push to S3"
# Output:
# Recommended skills to load:
# - skills/python/SKILL.md (confidence: high — Python task)
# - skills/aws/SKILL.md (confidence: high — S3 mentioned)
# - skills/git/SKILL.md (confidence: low — skip unless pushing to GitHub)Step 4: Apply to Memory Files Too
The same pattern works for memory and context files:
## Memory Loading (AGENTS.md)
At session start: Read MEMORY.md (summary only).
Load daily files (memory/YYYY-MM-DD.md) only when:
- User asks about past work
- Task references a specific date or project
- Debugging requires historical contextToken Savings Calculator
| Scenario | Before | After | Savings |
|---|---|---|---|
| 5 skills loaded | ~3,000 tokens | ~600 tokens | 80% |
| 10 skills loaded | ~6,500 tokens | ~750 tokens | 88% |
| 20 skills loaded | ~13,000 tokens | ~900 tokens | 93% |
| +Memory files (5) | +4,000 tokens | +400 tokens | 90% |
*Estimates based on average SKILL.md size of ~600 tokens. Catalog averages ~150 tokens.*
Integration with Token Optimizer
This skill pairs directly with OpenClaw Token Optimizer. Lazy loading handles context loading costs; Token Optimizer handles model routing, heartbeat budgeting, and runtime costs. Together they cover the full token lifecycle.
Install both:
clawhub install openclaw-skill-lazy-loader
clawhub install openclaw-token-optimizerFiles in This Skill
| File | Purpose |
|---|---|
SKILL.md | This guide |
SKILLS.md.template | Starter SKILLS catalog template |
AGENTS.md.template | Lazy loading AGENTS.md section |
context_optimizer.py | CLI helper — recommends skills to load per task |
README.md | ClawHub listing description |
SECURITY.md | Security audit and script disclosure |
.clawhubsafe | File integrity manifest |
Quick Start (5 minutes)
# 1. Install
clawhub install openclaw-skill-lazy-loader
# 2. Copy templates to your agent workspace
cp ~/.openclaw/skills/openclaw-skill-lazy-loader/SKILLS.md.template ~/my-agent/SKILLS.md
cp ~/.openclaw/skills/openclaw-skill-lazy-loader/AGENTS.md.template ~/my-agent/AGENTS.lazy.md
# 3. Edit SKILLS.md — fill in your actual skills
# 4. Merge AGENTS.lazy.md into your AGENTS.md
# 5. Test with context_optimizer.py
python3 ~/.openclaw/skills/openclaw-skill-lazy-loader/context_optimizer.py recommend "your next task"*By M Asif Rahman (@Asif2BD) · Apache 2.0 · https://clawhub.ai/Asif2BD/openclaw-skill-lazy-loader*