Results for “flow-actions”
9 skills
pranavnagrecha Agent Actions
Designs or reviews Agentforce agent actions, covering Flow, Apex invocable, and prompt-template actions, including naming, input/output contracts, confirmation, and error behavior.
15 · bundle
nvidia Tao Train Action Recognition
Train, evaluate, export, and run inference on TAO action-recognition models for classifying temporal actions in video clips using RGB, optical flow, or joint input.
2.2k · bundle
More results
dylanckawalec Mermate Openclaw MCP
Use when the user wants to build, extend, or debug the Python MCP bridge that exposes Mermate actions and stage flows to OpenClaw or other MCP clients.
3
jrennie99-glitch Agent Payments
Agent skill for payments - invoke with $agent-payments
0
jrennie99-glitch Agent Workflow
Agent skill for workflow - invoke with $agent-workflow
0
jrennie99-glitch Stream Chain
Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows
0
azusagasaku Lead Intelligence
AI 原生的潜在客户情报和外联流水线。用 agent 驱动的信号评分、共同关系人排名、暖场路径发现、来源语音建模和多渠道外联（邮件、LinkedIn、X），替代 Apollo、Clay 和 ZoomInfo。在用户想找到、评估并联系高价值联系人时使用。
0 · bundle
seb1n Human In The Loop
Design and verify auditable human oversight, approval gates, escalation paths, and safe state transitions for AI agent workflows. Use when deciding which agent actions require review, adding approve/reject or dual-control flows, preventing unauthorized autonomous effects, creating decision records, reducing rubber-stamping, or recovering safely from rejected, expired, or failed actions.
159 · bundle
aaaaqwq Guardian Angel
Guardian Angel gives AI agents a moral conscience rooted in Thomistic virtue ethics. Rather than relying solely on rule lists, it cultivates stable virtuous dispositions— prudence, justice, fortitude, temperance—that guide every interaction. The foundation is caritas: willing the good of the person you serve. From this flow the cardinal virtues as practical habits of right action and sound judgment. v3.0 introduced virtue-based disposition as the primary evaluation layer, providing deeper coherence than checklists alone. The agent's character becomes the safeguard. v3.1 adds: Plugin enforcement layer with before_tool_call hooks, approval workflows for ambiguous cases, and protections for sensitive infrastructure actions.
1 · bundle