Orchestrate multi-step AI workflows using OpenProse DSL and whipflow_run.
npx skills add https://github.com/npc-live/clawfirm --skill whipflow
Please help me install this Agent Skill. Skill: whipflow Source: https://github.com/npc-live/clawfirm/tree/main/cmd/clawfirm Command: npx skills add https://github.com/npc-live/clawfirm --skill whipflow
Automates the orchestration of multi-step AI workflows inside ClawFirm by coordinating steps, tools, and context.
Create a new workflow by writing a .whip file and run it with whipflow_run to orchestrate a multi-step AI task.
High-intent search queries and answers about installing and using this skill.
Multi-step AI workflows are orchestrated by defining step sequences, tool integrations, and context propagation using a domain-specific language. This coordinates stepwise decision making and automates complex pipelines like data analysis or research reports.
You define an automation workflow by writing a .whip file using the OpenProse DSL to sequence sessions and tool calls. You then execute it using the built-in run command, which processes the direct source without requiring external dependencies.
Yes, you can chain data gathering, analysis, and drafting steps into an end-to-end research-to-report pipeline. The orchestration coordinates these sequential sessions and propagates context across the automated workflow execution.
Yes, the DSL workflow execution handles inputs, retries, and permissions during execution. This ensures stepwise decision making and tool integration remain robust throughout the orchestrated automation tasks.
No, you do not need external dependencies to run a multi-step AI workflow. The built-in execution command runs the workflow directly from a file or source, handling the orchestration, step coordination, and context propagation natively.
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