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 agentsope/SkillAlchemy --skill agentsop-selfhost-decisiongit clone --depth 1 https://github.com/agentsope/SkillAlchemyWrote 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/agentsope/skillalchemy/agentsop-selfhost-decision)<a href="https://agentmods.dev/skills/agentsope/skillalchemy/agentsop-selfhost-decision"><img src="https://agentmods.dev/badge/skills/agentsope/skillalchemy/agentsop-selfhost-decision/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/agentsope/skillalchemy/agentsop-selfhost-decision"><img src="https://agentmods.dev/badge/skills/agentsope/skillalchemy/agentsop-selfhost-decision.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00093 | $0.07024 |
| Opus 5.5 | $0.00037 | $0.02810 |
| Sonnet 5.5 | $0.00019 | $0.01405 |
| Haiku 4.5 | $0.00009 | $0.00702 |
Grade A, and why
agentsop-selfhost-decision 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 1mo 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 — 311 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Self-host vs Managed-cloud Decision — A Project-Kickoff Rubric
Overlay, not a deep dive. This skill answers where to run (self-host vs managed), not which engine ([[agentsop-llm-engine-selection]]) or how to build the app ([[agentsop-dify]]). It fires first, at kickoff, and hands off to those once the side is chosen.
1. 何时激活 (When to Activate)
1.1 直接信号 (Direct triggers)
- At kickoff you must decide where an LLM or LLM platform runs: a managed API/cloud (OpenAI / Anthropic / Bedrock / Dify Cloud) vs your own GPUs / your own Docker (vLLM, self-hosted Dify).
- Cost pressure: monthly managed spend is climbing; someone says "should we just run our own and stop paying per token?"
- Compliance pressure: a data-residency / air-gap / regulated-data requirement (finance, medical, gov, GDPR region-lock) appears and the managed path is suddenly in question.
- You're comparing a self-hostable platform's tiers — e.g. Dify Cloud Pro ($59) vs self-deployed Docker [architjn.com/blog/dify-cloud-pricing-plans], or managed-vLLM-as-a-service vs your own H100s.
1.2 反向信号 (Skip this rubric when)
- The decision is already self-host, and the open question is which engine → go to [[agentsop-llm-engine-selection]] (vLLM vs TGI vs SGLang vs TensorRT-LLM vs llama.cpp).
- The decision is already self-host Dify, and the open question is how to build/operate it → go to [[agentsop-dify]].
- Single user / hobby / one stream — the answer is "just call the managed API"; no rubric needed.
- Training / fine-tuning siting — different cost structure (burst GPU, spot, not steady-state serving).
1.3 心智门槛 (Mental check)
This rubric exists because the loud reflex — "running our own is cheaper / more serious" — is true only above a volume crossover, and only if you have the ops capacity, and only if compliance hasn't already forced your hand. The job is to evaluate the gate before the slider, and to cost the ops burden, not just the GPU.
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.
- 1mo ago First seen · 311 lines · 93 tokens per session scan A 402fcada7f18
agentsop-selfhost-decision is a skill published in the GitHub repository agentsope/SkillAlchemy (445 stars, last pushed 14d ago), licensed MIT. It adds 93 tokens to every session and 7,024 once invoked, about $0.0004 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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