Menu

Individual skill

agentsop-selfhost-decision

Project-kickoff rubric for the self-host vs managed-cloud decision — when is running your own inference engine / LLM platform worth the ops cost vs paying per-token for a managed API? Decide on two axes — VOLUME (a cost-crossover slider) and COMPLIANCE (a hard gate). Use at kickoff when choosing where to run inference, or when cost / data-residency pressure forces a re-evaluation.

skills/agentsop-selfhost-decision/SKILL.md

Read pinned source

Source commit cf4376869e5f23f82404c3021a2a1315dfca318d

What was checked

Matches the observed repository HEAD
Yes
Scanner rules are current
No
Repository scan complete
No
Skill scan complete
No
Observed behavior
Not checked yet
Last checked
Nov 6, 2026

These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.

Install this skill

Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.

An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.

Repository context

Repository stars (not skill ratings)
465
Repository last updated
Oct 24, 2026
License
MIT

Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.

Files and excerpt

File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.

Browse files
Read excerpt

# 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.