What problem does it solve? Complex tasks handled by a single prompt often produce unreliable results because errors compound silently and intermediate reasoning is invisible. This Skill breaks work into fixed sequential LLM steps with validation gates between stages, so bad output is caught early and each stage stays focused on one job. ## Core Features & Use Cases - Sequential Step Decomposition: Split one task into ordered stages where each step has a single responsibility and a locked input/output schema. - Inter-Step Validation: Check output after every step with retry and stop rules, preventing bad early output from poisoning later stages. - Observability: Log step input, output, cost, and latency for each handoff to keep intermediate state traceable. - Use Case: When processing a long document, chain extract-facts → summarize-facts → draft-answer → check-answer-against-facts → format-output, validating each handoff instead of relying on one monolithic prompt. ## Quick Start Ask the AI to break your task into fixed sequential steps with a defined schema and validation check between each step using the prompt chaining pattern.