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/nobrainer-tech/langflow-mcp/optimize-memory-usagegit clone --depth 1 https://github.com/nobrainer-tech/langflow-mcpWhat 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 | $0.00016 | $0.00756 |
| Opus 5 | $0.00008 | $0.00378 |
| Sonnet 5 | $0.00003 | $0.00151 |
| Haiku 4.5 | $0.00002 | $0.00076 |
Grade A, and why
optimize-memory-usage 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.
How it starts
The opening of the file, as written. The whole thing — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Optimize Memory Usage
Analyze and optimize memory usage patterns to prevent leaks and improve application performance: $ARGUMENTS
Instructions
-
Memory Analysis and Profiling
- Profile current memory usage patterns using appropriate tools (Chrome DevTools, Node.js --inspect, Valgrind)
- Identify memory leaks and excessive memory consumption hotspots
- Analyze garbage collection patterns and performance impact
- Create baseline measurements for optimization tracking
- Document memory allocation hotspots and growth patterns over time
-
Memory Leak Detection
- Set up memory leak detection for different runtime environments
- Monitor heap snapshots and compare over time intervals
- Track DOM node leaks in browser applications
- Implement event listener cleanup and monitoring
- Use profiling tools to identify growing memory patterns
-
Garbage Collection Optimization
- Configure garbage collection settings for your runtime environment
- Tune Node.js heap sizes and GC flags for optimal performance
- Monitor GC pause times and frequency
- Implement GC performance monitoring and alerting
- Optimize object lifecycles to reduce GC pressure
-
Memory Pool and Object Reuse
- Implement object pooling for frequently allocated objects
- Create buffer pools for Node.js applications
- Reuse DOM elements and components in frontend applications
- Design memory-efficient data structures (circular buffers, sparse arrays)
- Pre-allocate objects to reduce runtime allocation overhead
-
String and Text Optimization
- Implement string interning for frequently used strings
- Optimize string concatenation and manipulation operations
- Use efficient text processing algorithms
- Minimize string duplication across the application
- Consider string compression for large text data
-
Database Connection Optimization
- Implement proper connection pooling with appropriate limits
- Configure connection timeouts and cleanup procedures
- Optimize query result caching and memory usage
- Monitor database connection memory overhead
- Implement connection leak detection and prevention
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 · 91 lines · 0 tokens per session scan A 1e783075e6e8
optimize-memory-usage is a command published in the GitHub repository nobrainer-tech/langflow-mcp (10 stars, last pushed 5d ago), licensed MIT. It adds 16 tokens to every session and 756 once invoked, about $0.0001 per session on Opus 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 2026-08-31.
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