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/florianbruniaux/claude-code-plugins/optimizegit clone --depth 1 https://github.com/FlorianBruniaux/claude-code-pluginsWhat 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 | $0.00015 | $0.01445 |
| Opus 5 | $0.00008 | $0.00723 |
| Sonnet 5 | $0.00003 | $0.00289 |
| Haiku 4.5 | $0.00002 | $0.00145 |
Grade A, and why
optimize scanned grade A with 1 finding 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
grep -rn "readFileSync\|writeFileSync\|execSync" --include="*.{ts,js}" . | head -10 How it starts
The opening of the file, as written. The whole thing — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Optimizer
Analyze and suggest performance improvements for code, queries, or systems.
Purpose
Identify optimization opportunities:
- Runtime performance bottlenecks
- Memory usage issues
- Database query inefficiencies
- Bundle size problems
- Algorithm complexity
Instructions
Step 1: Scope Identification
Determine optimization target:
- Function: Single function performance
- Module: Related functions/classes
- Query: Database query optimization
- Bundle: Frontend bundle analysis
- System: Architecture-level optimization
Step 2: Performance Analysis
Runtime Analysis
# Find potentially slow patterns
grep -rn "forEach\|\.map\|\.filter\|\.reduce" --include="*.{ts,js}" . | head -20
# Find nested loops (O(n²) potential)
grep -rn "for.*for\|\.forEach.*\.forEach\|\.map.*\.map" --include="*.{ts,js}" . | head -10
# Find sync operations that could be async
grep -rn "readFileSync\|writeFileSync\|execSync" --include="*.{ts,js}" . | head -10
Memory Analysis
# Large array operations
grep -rn "new Array\|Array\.from\|\.concat\|spread" --include="*.{ts,js}" . | head -10
# Potential memory leaks (event listeners, intervals)
grep -rn "addEventListener\|setInterval\|setTimeout" --include="*.{ts,js}" . | head -10
Database Query Analysis
# N+1 query patterns
grep -rn "await.*find\|await.*query" --include="*.{ts,js}" . | head -15
# Missing indexes hints
grep -rn "WHERE\|ORDER BY\|GROUP BY" --include="*.{ts,js,sql}" . | head -15
Bundle Analysis
# Check bundle size (if applicable)
[ -f "package.json" ] && npm run build 2>/dev/null && ls -lh dist/*.js 2>/dev/null
# Large dependencies
[ -f "package.json" ] && cat package.json | jq '.dependencies | keys[]' | head -20
Step 3: Prioritization
Rank findings by:
- Impact: How much will this improve performance?
- Effort: How hard is the fix?
- Risk: What could break?
Output Format
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 · 224 lines · 15 tokens per session scan A 784e2bedc265
optimize is a command published in the GitHub repository FlorianBruniaux/claude-code-plugins (40 stars, last pushed 2mo ago), licensed MIT. It adds 15 tokens to every session and 1,445 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
content-generate
Social media content generation command. Produces ready-to-use posts, captions, visual briefs, and hashtags for the given platform and type.
api-doc
API documentation generation. Scans route definitions and produces structured API docs.
aso
App Store Optimization command. iOS app listing analysis via the iTunes API, keyword optimization, and competitor comparison.
changelog
Automatic changelog generation. Produces a structured changelog from commit history.
coach
Coaching analysis command. Performs data-driven work-pattern analysis and offers personal improvement suggestions.
competitive-intel
Competitive analysis command. Analyzes the market, competitors, and opportunities with a comprehensive competitive-intelligence framework.