Chain individual skills into sequential or conditional agent pipelines.
npx skills add https://github.com/0xUrsanomics/utopia-os --skill skill-chaining
Please help me install this Agent Skill. Skill: skill-chaining Source: https://github.com/0xUrsanomics/utopia-os/tree/main/skills/skill-chaining Command: npx skills add https://github.com/0xUrsanomics/utopia-os --skill skill-chaining
This skill solves the fragmentation of complex tasks by allowing you to link multiple individual agent skills into a single, automated pipeline where context flows seamlessly from one step to the next.
Use the skill-chaining skill to execute the signal-to-content pipeline by providing the natural language request to turn the latest market signal into a drafted report.
High-intent search queries and answers about installing and using this skill.
Multi-step agent workflows are automated by chaining individual skills into sequential or conditional pipelines, passing accumulated context and outputs between discrete operational units to execute tasks end-to-end.
Conditional logic is supported in agent pipelines by creating branching paths based on step results, allowing actions like drafting content only when a preceding step scores a signal as HIGH.
Context transfer in sequential pipelines works by automatically passing the output of one skill as the input to the next, ensuring data continuity without manual intervention between operational units.
Automated agent pipelines require strict adherence to step-count limits and validation of skill existence within the registry to ensure execution safety and prevent workflow failures.
Existing skills in the registry are required before building an orchestration pipeline, as the system validates skill existence within the registry to ensure execution safety and proper workflow chaining.
epieczkoValidate command manifests and register slash commands in Betty.
ogallottiCoordinate a multi-agent workflow to create landing pages.
notqueCoordinate multiple skills into a validated execution DAG.
oaustegardCoordinate multiple AI agents to analyze code concurrently from security, performance, and architecture perspectives.
