bottleneck-detect

A bottleneck detector for swarm operations that examines delays, agent response times, task completion, parallel work, memory access, and resource contention.

In plain words
What is it for?
Use it to inspect the current or a specific swarm over a chosen time range, set the percentage threshold for reporting issues, export findings, or run automatic fixes.
Why use it?
It helps locate parts of a multi-agent workflow that slow the whole swarm down and can optionally apply automatic optimizations.

Command for Claude Code

Install

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.

agentmods
npx agentmods add commands/ruvnet/ruview/bottleneck-detect
Clone the repo
git clone --depth 1 https://github.com/ruvnet/RuView

Made for: Claude Code.

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 874 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.00874
Opus 5 $0.00000 $0.00437
Sonnet 5 $0.00000 $0.00175
Haiku 4.5 $0.00000 $0.00087

Measured 3d ago against content hash 2873e9bdeb14, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

bottleneck-detect 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 3d 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.

Origin

Copies of this mod

8 near-identical copies found in the catalogue:

.claude/commands/analysis/bottleneck-detect.md · 163 lines

How it starts

The opening of the file, as written. The whole thing — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.

bottleneck detect

Analyze performance bottlenecks in swarm operations and suggest optimizations.

Usage

npx claude-flow bottleneck detect [options]

Options

  • --swarm-id, -s <id> - Analyze specific swarm (default: current)
  • --time-range, -t <range> - Analysis period: 1h, 24h, 7d, all (default: 1h)
  • --threshold <percent> - Bottleneck threshold percentage (default: 20)
  • --export, -e <file> - Export analysis to file
  • --fix - Apply automatic optimizations

Examples

Basic bottleneck detection

npx claude-flow bottleneck detect

Analyze specific swarm

npx claude-flow bottleneck detect --swarm-id swarm-123

Last 24 hours with export

npx claude-flow bottleneck detect -t 24h -e bottlenecks.json

Auto-fix detected issues

npx claude-flow bottleneck detect --fix --threshold 15

Metrics Analyzed

Communication Bottlenecks

  • Message queue delays
  • Agent response times
  • Coordination overhead
  • Memory access patterns

Processing Bottlenecks

  • Task completion times
  • Agent utilization rates
  • Parallel execution efficiency
  • Resource contention

Memory Bottlenecks

  • Cache hit rates
  • Memory access patterns
  • Storage I/O performance
  • Neural pattern loading

Network Bottlenecks

  • API call latency
  • MCP communication delays
  • External service timeouts
  • Concurrent request limits

Output Format

🔍 Bottleneck Analysis Report
━━━━━━━━━━━━━━━━━━━━━━━━━━━

📊 Summary
├── Time Range: Last 1 hour
├── Agents Analyzed: 6
├── Tasks Processed: 42
└── Critical Issues: 2

🚨 Critical Bottlenecks
1. Agent Communication (35% impact)
   └── coordinator → coder-1 messages delayed by 2.3s avg

2. Memory Access (28% impact)
   └── Neural pattern loading taking 1.8s per access

⚠️ Warning Bottlenecks
1. Task Queue (18% impact)
   └── 5 tasks waiting > 10s for assignment

💡 Recommendations
1. Switch to hierarchical topology (est. 40% improvement)
2. Enable memory caching (est. 25% improvement)
3. Increase agent concurrency to 8 (est. 20% improvement)

✅ Quick Fixes Available
Run with --fix to apply:
- Enable smart caching
- Optimize message routing
- Adjust agent priorities

Read the full file on GitHub · 163 lines

Changes

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.

  1. 3d ago First seen · 163 lines · 0 tokens per session scan A 2873e9bdeb14

Subscribe to this mod's changes

bottleneck-detect is a command published in the GitHub repository ruvnet/RuView (92,289 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 874 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.