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.
git clone --depth 1 https://github.com/monoes/monomindWrote 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/monoes/monomind/bottleneck-detect)<a href="https://agentmods.dev/commands/monoes/monomind/bottleneck-detect"><img src="https://agentmods.dev/badge/commands/monoes/monomind/bottleneck-detect/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/monoes/monomind/bottleneck-detect"><img src="https://agentmods.dev/badge/commands/monoes/monomind/bottleneck-detect.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 | $0.00019 | $0.00356 |
| Opus 5.5 | $0.00008 | $0.00142 |
| Sonnet 5.5 | $0.00004 | $0.00071 |
| Haiku 4.5 | $0.00002 | $0.00036 |
Grade A, and why
analysis: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 yesterday.
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.
What it actually says
bottleneck-detect
Detect performance bottlenecks in system components and swarm operations.
Usage
npx monomind performance bottleneck [options]
Options
--component, -c <name>- Analyze a specific component (e.g.memory,neural,swarm)--depth, -d <level>- Analysis depth:quick(default) orfull
Examples
Quick bottleneck scan
npx monomind performance bottleneck
Deep analysis of a specific component
npx monomind performance bottleneck --component memory --depth full
Metrics Analyzed
Processing Bottlenecks
- CPU load and utilization
- Memory pressure and heap usage
- Disk I/O latency
Swarm Bottlenecks
- Agent coordination overhead
- Task queue depth and wait times
- Parallel execution efficiency
Memory Bottlenecks
- Cache hit rates
- Neural pattern load time
- Storage I/O performance
Integration with Claude Code
mcp__monomind__performance_bottleneck({
component: "memory", // optional — omit to scan all
threshold: 20, // alert threshold %
deep: false // set true for full analysis
})
See Also
performance metrics— detailed time-series metricsperformance optimize— apply recommended fixesperformance benchmark— run benchmark suitestoken-usage— token consumption analysis
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.
- yesterday First seen · 71 lines · 19 tokens per session scan A bf5682aef9e8
analysis:bottleneck-detect is a command published in the GitHub repository monoes/monomind (23 stars, last pushed yesterday), licensed Apache-2.0. It adds 19 tokens to every session and 356 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-10-26.
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