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llm-pipeline

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Use when wiring several LLM calls into a production flow: typed contracts between steps, a router/gateway so 429s, timeouts and outages fail over instead of taking you down, and cost control via caching, model tiers and abort caps. NOT single-prompt wording (that is `prompt-engineering`), NOT a model-driven tool loop (that is `building-agents`).

skills/llm-pipeline/SKILL.md

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Nov 9, 2026
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# llm-pipeline

Wire multiple LLM calls into a reliable, controllable production pipeline. You chain steps where one call's validated output feeds the next, put a router in front of providers so an outage fails over instead of taking you down, and engineer the cross-cutting concerns: timeouts, bounded retries, fallbacks, caching, and cost caps.

Treat the LLM as an unreliable network dependency, not a local function call. Every rule below follows from that: providers have outages, rate limits, and latency tails, so no single provider is a single point of failure and no call is allowed to run unbounded.

## Do you even need a pipeline?

This skill is the orchestration *around* calls. If you only have one call, you are in the wrong place.

| Situation | Go to |
| --- | --- |
| Make one prompt better, few-shot, system-prompt design | [../prompt-engineering/SKILL.md](../prompt-engineering/SKILL.md) |
| One call must return a typed object validated against a schema | [../structured-extraction/SKILL.md](../structured-extraction/SKILL.md) |
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