Results for “handoff”

Compact the current conversation into a handoff document for another agent to pick up.

Compact the current conversation into a handoff document for another agent to pick up.

Compact the current conversation into a handoff document a fresh agent can pick up. User-invoked via /handoff; an optional argument describes what the next session will focus on.

Compact the current conversation into a handoff document for another agent to pick up.

Compact the current conversation into a handoff document for another agent to pick up.

Compact the current conversation into a handoff document for another agent to pick up.

Creates comprehensive handoff documents for seamless AI agent session transfers. Triggered when: (1) user requests handoff/memory/context save, (2) context window approaches capacity, (3) major task milestone completed, (4) work session ending, (5) user says 'save state', 'create handoff', 'I need to pause', 'context is getting full', (6) resuming work with 'load handoff', 'resume from', 'continue where we left off'. Proactively suggests handoffs after substantial work (multiple file edits, complex debugging, architecture decisions). Solves long-running agent context exhaustion by enabling fresh agents to continue with zero ambiguity.

Hand off tasks to the SLICC browser agent or install a new skill into SLICC from a GitHub repository.

Automate Zeplin design handoff tasks by discovering and executing tools through the Rube MCP interface.

Write concise next-agent handoff summaries across sessions, tools, and coding agents. Load when the user says handoff, next agent should know, save context, summarize where we are, switching agents, before ending a meaningful session, or when the user asks to commit, push, commit and push, create a git commit, push to origin, or publish commits — commit/push requests MUST run this skill first to prepare handoff docs, then proceed with git operations.

Compacts the current conversation into a handoff document for another agent to pick up. Use when the user says "hand this off" or wants the work continued by a fresh session.

Compact the current conversation into a handoff document for another agent to pick up. Use when user wants to hand off work, summarize progress, or prepare context for a new session.

Compact the current session into a single detailed handoff message that can be pasted into a fresh agent run. Use when switching context, ending a session, or avoiding context-window loss.

Creates temporary encrypted one-time handoffs between autonomous agents, supporting mission briefs, scoped secrets, artifacts, and receipts via CLI or API.

Hand off the current task to another agent with full context. Use when the user says "handoff", "hand off", "hand this to", or wants to pass work to another agent (Codex or Claude).

Use when passing work, tasks, or deliverables between agents. This skill provides a standardized protocol for agent-to-agent handoffs, ensuring context, requirements, and expectations are clearly communicated during task delegation or escalation.

Scaffolds VS Code custom agent files (.agent.md) with YAML frontmatter, tool configuration, handoffs, and instructions for specialized AI personas.

Package an in-progress task on this cluster so a Claude agent on another cluster (MMM Young, CX3, HX1, Isambard) can pick it up, or resume a task handed off to this cluster. Use when the user says hand off / migrate / continue this on <cluster>, or asks you to pick up an existing handoff.

Compact the current conversation into a handoff document for another agent to pick up. References existing artifacts (PRDs, plans, ADRs, issues, commits, diffs) by path or URL instead of duplicating them. Use when user wants to hand off the conversation to a fresh agent or starts a new session that picks up prior work.

End-of-session context handoff. Saves session state so the next session or a parallel agent can pick up exactly where the left off. Run this when context is getting full (~80%) or before stopping work.

Provides detailed guidance on Hermes Kanban worker lifecycle, including workspace handling, handoff patterns, retry diagnostics, and edge cases for dispatched workers.

Hands the current conversation to a fresh background agent that picks up the work immediately. Use when the user wants the work continued by a background agent.

Compact the current conversation into a handoff document so a fresh agent can pick up the work with zero prior context. Use when the user wants to end a session and continue later, is running low on context, says "write a handoff", "hand this off", "summarize for the next session", "compact this", or wants to transfer work to another agent or teammate.

Compact the current conversation into a handoff document for another agent to pick up. Save to a user-configured location (OS temp, home folder, or per-project .handoff/), redact secrets before write, suggest skills for the next session, and auto-load the latest handoff on the next SessionStart. First-run setup asks where to save so the project folder never gets cluttered. Use when the user says 'hand this off', 'handoff doc', 'summarize this for a new session', 'compact this conversation', 'I'm ending this session', 'pick this up later', or any variation signaling intent to pass work to a fresh agent. Also trigger on implicit signals: the user announcing they're switching machines, ending the day mid-task, or context is growing long without a natural stopping point.

Hand the current conversation off to a fresh background agent that picks up the work immediately.

Offload sub-tasks to other agents, specialist models, or background jobs, with guidance on choosing the right method and verifying results.

Scaffold and develop AI agents using OpenAI Agents SDK patterns, covering agent definition, tools, guardrails, handoffs, context, RAG pipelines, streaming, API routes, testing, and debugging.

Orchestrate multi-agent workflows with task decomposition, role assignment, handoff protocols, and per-session context budgeting.

Design task-local harnesses, eval gates, and reusable skill extraction for adaptive agent workflows.

Discovers, audits, repairs, adapts, and designs bounded AI-agent loops with explicit triggers, actions, verification, stopping conditions, guardrails, and handoffs.