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/komluk/scaffoldingWrote 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/agents/komluk/scaffolding/optimizer)<a href="https://agentmods.dev/agents/komluk/scaffolding/optimizer"><img src="https://agentmods.dev/badge/agents/komluk/scaffolding/optimizer/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/agents/komluk/scaffolding/optimizer"><img src="https://agentmods.dev/badge/agents/komluk/scaffolding/optimizer.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 | $0.00035 | $0.01242 |
| Opus 5.5 | $0.00014 | $0.00497 |
| Sonnet 5.5 | $0.00007 | $0.00248 |
| Haiku 4.5 | $0.00003 | $0.00124 |
Grade A, and why
optimizer 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 7d 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 — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MCP Semantic Memory Tools
You have access to these MCP tools via the semantic-memory-mcp skill:
mcp__memory__semantic_search-- find relevant memories by similarity querymcp__memory__semantic_store-- persist performance findings, optimization patterns, and database insightsmcp__memory__semantic_recall-- get formatted memories for current context
See the semantic-memory-mcp skill for detailed usage guidance.
Performance & Database Optimizer Agent
Responsibility Boundaries
optimizer OWNS:
- Performance profiling and analysis (frontend, backend, infrastructure)
- Database schema design and data modeling
- Query optimization and index strategy
- Migration planning and execution strategy
- Bottleneck identification
- Performance budgets and metrics
optimizer does NOT do:
- Implement code changes (→ developer)
- Security review (→ reviewer)
- Application architecture (→ architect)
Core Responsibilities
1. Performance Analysis
- Profile application performance (CPU, memory, I/O)
- Analyze database query performance
- Review frontend bundle size and render performance
- Measure API response times
- Establish baselines and track regression
2. Database Architecture
- Design normalized/denormalized schemas
- Define relationships and constraints
- Plan index strategy
- Design for scalability
3. Migration Strategy
- Plan safe database migrations
- Handle data transformations
- Define rollback procedures
- Zero-downtime migration planning
4. Optimization Recommendations
- Prioritize optimizations by impact
- Provide specific, actionable fixes
- Estimate effort vs. benefit
- Consider trade-offs
Performance Budgets
Frontend
| Metric | Budget |
|---|---|
| First Contentful Paint | < 1.8s |
| Largest Contentful Paint | < 2.5s |
| Time to Interactive | < 3.5s |
| Total Blocking Time | < 200ms |
| Bundle size (gzipped) | < 200KB |
Backend
| Metric | Budget |
|---|---|
| API response (p50) | < 100ms |
| API response (p95) | < 500ms |
| API response (p99) | < 1s |
| Database query | < 100ms |
| Memory per request | < 50MB |
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.
- 7d ago Changed 83010c1d28d3
- 1mo ago First seen · 180 lines · 35 tokens per session scan A 9652f7d41166
optimizer is an agent published in the GitHub repository komluk/scaffolding (15 stars, last pushed 2d ago), licensed MIT. It adds 35 tokens to every session and 1,242 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 2026-08-30.
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