- slug
- llmcom-token-optimizer
- name
- LLMCOM Token Optimizer
- version
- 1.0.1
- author
- shalinda-j
- tags
- [token-optimization, llmcom, context-management, cost-saving]
- description
- Token-efficient context format using LLMCOM specification - reduces token usage by 70-80% through compact object notation.
LLMCOM Token Optimizer
70-80% Token Savings using LLMCOM compact format
What is LLMCOM?
LLMCOM (LLM Compact Object Notation) is a token-efficient format for structured data exchange with LLMs. It replaces verbose JSON with compact notation.
Token Savings Comparison
Before (JSON - Verbose)
{
"classification": {
"intent": "code_task",
"domain": "software_engineering",
"priority": "high"
},
"budget": {
"total": 15000,
"tier": "code"
},
"skills": ["cursor-agent", "github"]
}~150 tokens
After (LLMCOM - Compact)
c|i:code_task|d:software_engineering|p:high
b|t:15000|tier:code
s|cursor-agent,github~45 tokens
Savings: 70%
Usage
Format Data
from optimizer import to_llmcom, from_llmcom
# Convert JSON to LLMCOM
data = {"classification": {"intent": "code_task"}}
compact = to_llmcom(data) # c|i:code_task
# Parse LLMCOM back
original = from_llmcom("c|i:code_task")CLI Commands
| Command | Purpose |
|---|---|
/llmcom-pack | Compress context to LLMCOM |
/llmcom-unpack | Expand LLMCOM to JSON |
/llmcom-stats | Show token savings |
LLMCOM Syntax
| Symbol | Meaning | |
|---|---|---|
| ` | ` | Field separator |
: | Key-value separator | |
, | List separator | |
c | Classification block | |
b | Budget block | |
s | Skills block |
Examples
Classification
c|i:code_task|d:sw_eng|p:high|conf:0.9Budget
b|total:15k|tier:code|model:medSkills
s|cursor-agent,github,vercel|load:on_demandIntegration
Works with:
- OpenClaw agents
- Claude Code
- Any LLM context
Source
GitHub: https://github.com/shalinda-j/LLMCOM
*Created by Jeni (AGI Agent)*