Ruflo is an execution and coordination layer for Claude Code and Codex that equips AI coding agents with tools, memory, control loops, sandboxes, and collaboration mechanisms. Developers use it to organize specialized agents into swarms, coordinate workflows, retain knowledge across sessions, and communicate across machines. The catalogue entries are Ruflo’s skills, commands, agents, hooks, and plugin components.
Borrowing it
Nothing to install: this file belongs to ruvnet/ruflo. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ruvnet/ruflo/main/.claude/commands/analysis/token-efficiency.mdgit clone --depth 1 https://github.com/ruvnet/rufloWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/ruvnet/ruflo/token-efficiency)<a href="https://agentmods.dev/commands/ruvnet/ruflo/token-efficiency"><img src="https://agentmods.dev/badge/commands/ruvnet/ruflo/token-efficiency/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/ruvnet/ruflo/token-efficiency"><img src="https://agentmods.dev/badge/commands/ruvnet/ruflo/token-efficiency.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00000 | $0.00247 |
| Opus 5.5 | $0.00000 | $0.00099 |
| Sonnet 5.5 | $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 1mo 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.
This is a copy
100% identical to token-efficiency — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
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.
- 1mo ago First seen · 45 lines · 0 tokens per session scan A ecb6c03b491c
token-efficiency is a command published in the GitHub repository ruvnet/ruflo (75,624 stars, last pushed today), 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. It is 100% identical to token-efficiency, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
briefing
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help
Show complete BetterCallClaude command reference, available agents, skills, and usage examples.
legal-goal
Define a checkable legal success condition for /legal-loop. Accepts a named profile (citations-clean, draft-passes-gate, adversarial-converge, nda-batch-clean, reg-watch, timeline-sourced) or free-text objective. Produces a persisted Goal Record — never starts work itself.
legal-way
Work one ticket from a legal-wayfinder decision map — claim a frontier ticket, resolve it by type (research / grilling / prototype / task), record the decision, graduate newly-sharp fog, and emit the handoff pack when the map is clear.
create-workflow
Create a reusable custom workflow by combining BetterCallClaude agents. Interview-based: pick agents, order them, define the output. Saved for future use with /bettercallclaude:workflow.
legal-chart
Chart a big legal matter as a wayfinder decision map — grill the attorney breadth-first, create the map and decision tickets, fire research tickets in parallel. Planning only: charting resolves no decisions itself.