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 skills add henryalouf/ruflow --skill agent-adaptive-coordinatorgit clone --depth 1 https://github.com/henryalouf/ruflowWrote 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/skills/henryalouf/ruflow/agent-adaptive-coordinator)<a href="https://agentmods.dev/skills/henryalouf/ruflow/agent-adaptive-coordinator"><img src="https://agentmods.dev/badge/skills/henryalouf/ruflow/agent-adaptive-coordinator/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/skills/henryalouf/ruflow/agent-adaptive-coordinator"><img src="https://agentmods.dev/badge/skills/henryalouf/ruflow/agent-adaptive-coordinator.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 | $0.00021 | $0.03379 |
| Opus 5 | $0.00010 | $0.01690 |
| Sonnet 5 | $0.00004 | $0.00676 |
| Haiku 4.5 | $0.00002 | $0.00338 |
Grade A, and why
agent-adaptive-coordinator 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 9d 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 agent-adaptive-coordinator — 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.
How it starts
The opening of the file, as written. The whole thing — 401 lines — stays where its author put it; the contents beside it link to each section on GitHub.
name: adaptive-coordinator
type: coordinator
color: "#9C27B0"
description: Dynamic topology switching coordinator with self-organizing swarm patterns and real-time optimization
capabilities:
- topology_adaptation
- performance_optimization
- real_time_reconfiguration
- pattern_recognition
- predictive_scaling
- intelligent_routing
priority: critical
hooks:
pre: |
echo "🔄 Adaptive Coordinator analyzing workload patterns: $TASK"
Initialize with auto-detection
mcp__claude-flow__swarm_init auto --maxAgents=15 --strategy=adaptiveAnalyze current workload patterns
mcp__claude-flow__neural_patterns analyze --operation="workload_analysis" --metadata="{"task":"$TASK"}"Train adaptive models
mcp__claude-flow__neural_train coordination --training_data="historical_swarm_data" --epochs=30Store baseline metrics
mcp__claude-flow__memory_usage store "adaptive:baseline:${TASK_ID}" "$(mcp__claude-flow__performance_report --format=json)" --namespace=adaptiveSet up real-time monitoring
mcp__claude-flow__swarm_monitor --interval=2000 --swarmId="${SWARM_ID}" post: | echo "✨ Adaptive coordination complete - topology optimized"Generate comprehensive analysis
mcp__claude-flow__performance_report --format=detailed --timeframe=24hStore learning outcomes
mcp__claude-flow__neural_patterns learn --operation="coordination_complete" --outcome="success" --metadata="{"final_topology":"$(mcp__claude-flow__swarm_status | jq -r '.topology')"}"Export learned patterns
mcp__claude-flow__model_save "adaptive-coordinator-${TASK_ID}" "$tmp$adaptive-model-$(date +%s).json"Update persistent knowledge base
mcp__claude-flow__memory_usage store "adaptive:learned:${TASK_ID}" "$(date): Adaptive patterns learned and saved" --namespace=adaptive
Adaptive Swarm Coordinator
You are an intelligent orchestrator that dynamically adapts swarm topology and coordination strategies based on real-time performance metrics, workload patterns, and environmental conditions.
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.
- 9d ago First seen · 401 lines · 21 tokens per session scan A 8fe3c7c499d1
agent-adaptive-coordinator is a skill published in the GitHub repository henryalouf/ruflow (126 stars, last pushed 3mo ago), licensed MIT. It adds 21 tokens to every session and 3,379 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to agent-adaptive-coordinator, differing in 0 lines, and is treated as a copy.
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