Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/ruvnet/ruview/token-efficiencygit clone --depth 1 https://github.com/ruvnet/RuViewWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00000 | $0.00247 |
| Opus 5 | $0.00000 | $0.00123 |
| Sonnet 5 | $0.00000 | $0.00049 |
| Haiku 4.5 | $0.00000 | $0.00025 |
Grade A, and why
token-efficiency scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
8 near-identical copies found in the catalogue:
- token-efficiency — 100% identical, 0 lines differ
- token-efficiency — 100% identical, 0 lines differ
- token-efficiency — 100% identical, 0 lines differ
- token-efficiency — 100% identical, 0 lines differ
- token-efficiency — 100% identical, 0 lines differ
- token-efficiency — 100% identical, 0 lines differ
- token-efficiency — 100% identical, 0 lines differ
- token-efficiency — 100% identical, 0 lines differ
What it actually says
Token Usage Optimization
Purpose
Reduce token consumption while maintaining quality through intelligent coordination.
Optimization Strategies
1. Smart Caching
- Search results cached for 5 minutes
- File content cached during session
- Pattern recognition reduces redundant searches
2. Efficient Coordination
- Agents share context automatically
- Avoid duplicate file reads
- Batch related operations
3. Measurement & Tracking
# Check token savings after session
Tool: mcp__claude-flow__token_usage
Parameters: {"operation": "session", "timeframe": "24h"}
# Result shows:
{
"metrics": {
"tokensSaved": 15420,
"operations": 45,
"efficiency": "343 tokens/operation"
}
}
Best Practices
- Use Task tool for complex searches
- Enable caching in pre-search hooks
- Batch operations when possible
- Review session summaries for insights
Token Reduction Results
- 📉 32.3% average token reduction
- 🎯 More focused operations
- 🔄 Intelligent result reuse
- 📊 Cumulative improvements
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 45 lines · 0 tokens per session scan A ecb6c03b491c
token-efficiency is a command published in the GitHub repository ruvnet/RuView (92,079 stars, last pushed 2d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 247 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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