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 selvarajmurugesan90/ops-engineering-skills --skill complete-ai-agent-stack-deployment-self-hosted-from-scratchgit clone --depth 1 https://github.com/selvarajmurugesan90/ops-engineering-skillsWrote 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/selvarajmurugesan90/ops-engineering-skills/complete-ai-agent-stack-deployment-self-hosted-from-scratch)<a href="https://agentmods.dev/skills/selvarajmurugesan90/ops-engineering-skills/complete-ai-agent-stack-deployment-self-hosted-from-scratch"><img src="https://agentmods.dev/badge/skills/selvarajmurugesan90/ops-engineering-skills/complete-ai-agent-stack-deployment-self-hosted-from-scratch/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/selvarajmurugesan90/ops-engineering-skills/complete-ai-agent-stack-deployment-self-hosted-from-scratch"><img src="https://agentmods.dev/badge/skills/selvarajmurugesan90/ops-engineering-skills/complete-ai-agent-stack-deployment-self-hosted-from-scratch.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 6 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 69 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 102 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 325 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 121 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 326 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 193 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00217 | $0.04299 |
| Opus 5 | $0.00109 | $0.02150 |
| Sonnet 5 | $0.00043 | $0.00860 |
| Haiku 4.5 | $0.00022 | $0.00430 |
Grade A, and why
complete-ai-agent-stack-deployment-self-hosted-from-scratch 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 12d 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 — 334 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Complete AI Agent Stack Deployment (Self-Hosted) From Scratch
Purpose
The cloud-managed AI agent path in this skill family leans on managed LLM provider APIs and a managed vector database, trading infrastructure ownership for per-token pricing and someone else's on-call rotation. This skill is the opposite path: serving an open-weight model on GPU infrastructure the team itself procures and operates, paired with a self-hosted vector database and self-hosted MCP servers, with no managed LLM API or managed vector database anywhere in the stack. The tradeoff is real, and the sequencing risk is sharper than on the managed path: GPU capacity has to be sized and provisioned before the agent's latency budget is even meaningfully designable (unlike a managed API, where provider-side scaling is someone else's problem), and every durability concern a managed vector database absorbs — replication, backup, upgrade — becomes this team's responsibility from day one. This skill sequences that whole path — GPU procurement through evaluation — and is explicit throughout about where the self-hosted burden actually lands.
When to use
- Standing up a production AI agent with a hard requirement of no managed LLM API or managed vector database — data residency, air-gapped deployment, fixed-cost GPU amortization, or model-customization reasons all commonly drive this.
- Deciding whether a team genuinely has the GPU procurement and operational capacity to self-host an agent stack, versus one of the cloud-managed alternatives in this skill family.
- Auditing an existing self-hosted agent deployment for a skipped or out-of-order phase (e.g. an agent's latency budget designed before real serving latency was measured on actual hardware, or a self-hosted vector database with no replication running in production for months).
- Rebuilding a reference self-hosted agent architecture for a second team or environment that should follow the same proven sequence as a known-good first deployment.
- Honestly comparing the total cost and operational burden of this path against the cloud-managed alternative before committing to it.
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.
- 12d ago First seen · 334 lines · 217 tokens per session scan A 16302d63a4f8
complete-ai-agent-stack-deployment-self-hosted-from-scratch is a skill published in the GitHub repository selvarajmurugesan90/ops-engineering-skills (39 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 217 tokens to every session and 4,299 once invoked, about $0.0011 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 2026-08-30.
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