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 skills add williamzujkowski/standards --skill model-deploymentgit clone --depth 1 https://github.com/williamzujkowski/standardsWrote 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/skills/williamzujkowski/standards/model-deployment)<a href="https://agentmods.dev/skills/williamzujkowski/standards/model-deployment"><img src="https://agentmods.dev/badge/skills/williamzujkowski/standards/model-deployment/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/skills/williamzujkowski/standards/model-deployment"><img src="https://agentmods.dev/badge/skills/williamzujkowski/standards/model-deployment.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 | $0.00016 | $0.00445 |
| Opus 5.5 | $0.00006 | $0.00178 |
| Sonnet 5.5 | $0.00003 | $0.00089 |
| Haiku 4.5 | $0.00002 | $0.00044 |
Grade A, and why
model-deployment 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- model-development — 89% identical, 6 lines differ
What it actually says
Model Deployment
Quick Navigation: Level 1: Quick Start (5 min) → Level 2: Implementation (30 min) → Level 3: Mastery (Extended)
Level 1: Quick Start
Core Principles
- Best Practices: Follow industry-standard patterns for ml ai
- Security First: Implement secure defaults and validate all inputs
- Maintainability: Write clean, documented, testable code
- Performance: Optimize for common use cases
Essential Checklist
- Follow established patterns for ml ai
- Implement proper error handling
- Add comprehensive logging
- Write unit and integration tests
- Document public interfaces
Quick Links to Level 2
Level 2: Implementation
Core Concepts
This skill covers essential practices for ml ai.
Key areas include:
- Architecture patterns
- Implementation best practices
- Testing strategies
- Performance optimization
Implementation Patterns
Apply these patterns when working with ml ai:
- Pattern Selection: Choose appropriate patterns for your use case
- Error Handling: Implement comprehensive error recovery
- Monitoring: Add observability hooks for production
Common Pitfalls
Avoid these common mistakes:
- Skipping validation of inputs
- Ignoring edge cases
- Missing test coverage
- Poor documentation
Level 3: Mastery Resources
Reference Materials
Templates
See the templates/ directory for starter configurations.
External Resources
Consult official documentation and community best practices for ml ai.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 84 lines · 16 tokens per session scan A 0ed0cf74071f
model-deployment is a skill published in the GitHub repository williamzujkowski/standards (18 stars, last pushed 1mo ago), licensed MIT. It adds 16 tokens to every session and 445 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 2026-09-29.
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