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/clchinkc/document-mcp/10-optimization-finalizationgit clone --depth 1 https://github.com/clchinkc/document-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 | $0.00000 | $0.00626 |
| Opus 5 | $0.00000 | $0.00313 |
| Sonnet 5 | $0.00000 | $0.00125 |
| Haiku 4.5 | $0.00000 | $0.00063 |
Grade A, and why
10-optimization-finalization 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.
How it starts
The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
System Optimization & Release Finalization
Comprehensive Optimization: Multi-agent optimization, PRD improvement, documentation consolidation, and production-ready finalization.
Phase 1: Multi-Agent Optimization Round Robin
Use diverse specialized agents for comprehensive system optimization:
Architecture & Performance:
- Backend Architect: System design optimization, service architecture, API design
- Performance Optimizer: Performance bottlenecks, caching strategies, resource optimization
- Frontend System Builder: UI/UX optimization, component architecture, user experience
- AI Engineer: ML/AI system optimization, model performance, intelligent features
Quality & Security:
- QA Engineer: Quality assurance processes, testing optimization, defect prevention
- Security Auditor: Security hardening, vulnerability assessment, privacy compliance
- Code Refactoring Specialist: Code quality, maintainability, architectural improvements
Planning & Documentation:
- Behavior Analyst: User behavior analysis, requirement validation, scenario optimization
- Sprint Prioritizer: Feature prioritization, release planning, roadmap optimization
Phase 2: PRD & Documentation Enhancement
PRD Improvement Process:
- Research current documentation and integrate insights organically, logically, naturally
- Ultrathink critique, evaluate, and discuss structural improvements
- Keep organization coherent and logical with concise formatting
- Maintain original wording and content details while improving information density
- Output everything in English with ALL existing details preserved
- Keep remaining content in original language where specified
Documentation Consolidation:
- Consolidate all recent modifications into current status sections
- Eliminate "recent modification" sections - integrate changes organically
- Update all documentation based on system modifications
- Ensure documentation accuracy reflects actual implementation
- Prepare documentation for production release
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 · 69 lines · 0 tokens per session scan A 1bc4b9581d15
10-optimization-finalization is a command published in the GitHub repository clchinkc/document-mcp (0 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 626 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 2026-08-31.
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