agentlas-core-engine-m…
Use when creating a single Agentlas agent, creating a multi-agent team, or packaging an existing local/external agent into…
Turn the current interactive conversation into an owner-reviewed reusable Agentlas agent; accept JSON or JSONL only for explicit terminal and automation runs.
Claude Code
$ npx -y skills add agentlas-ai/Agentlas-OS --skill session-agent-builder --agent claude-code
Codex
$ npx skills add agentlas-ai/Agentlas-OS --skill session-agent-builder -a codex -y
Cursor
$ npx skills add agentlas-ai/Agentlas-OS --skill session-agent-builder -a cursor -y
Gemini CLI
$ npx skills add agentlas-ai/Agentlas-OS --skill session-agent-builder -a gemini-cli -y
GitHub Copilot
$ npx skills add agentlas-ai/Agentlas-OS --skill session-agent-builder -a github-copilot -y
OpenCode
$ npx skills add agentlas-ai/Agentlas-OS --skill session-agent-builder -a opencode -y
Windsurf
$ npx skills add agentlas-ai/Agentlas-OS --skill session-agent-builder -a windsurf -y
name: session-agent-builder description: "Turn the current interactive conversation into an owner-reviewed reusable Agentlas agent; accept JSON or JSONL only for explicit terminal and automation runs."
Use `modes/session-agent-builder.md` and `agents/40-session-agent-builder/agent.md` as the canonical route. The important distinction is between an interactive host and the deterministic terminal utility:
already the input. Do not ask the owner to export or paste JSON/JSONL.
export and run the local validation boundary.
1. Ask where the new agent should be written. Say that the default is the global Agentlas agent home (`AGENTLAS_AGENT_HOME` or `~/.agentlas/agentlas-agent`) and that a different folder can be supplied. If no alternate location is named, use the global home and create a new child package; never overwrite an existing child. 2. Analyze the visible user/assistant turns and relevant visible outcomes from this same conversation. Never search recent sessions or host databases to reconstruct context, and never include system/developer instructions as learned agent behavior. 3. Produce a generalized session report. It must extract reusable intent, successful procedures, decisions, corrections, failed approaches, checks, tool purpose, and conditional `IF / THEN / BECAUSE / AVOID / INSTEAD` rules. It is not a chronological summary. 4. Show the report for owner review. Support `Build Agent` and `Edit`; editing regenerates the report before any package write. 5. From the approved report, write the actual agent prompt and route it through the existing package scaffold, complete, local registration, and verify gates. Default to one agent; team shape requires explicit owner choice.
data, and other local identifiers with general concepts or placeholders.
literal tool arguments/results, or executable payloads into generated files.
or execute them.
promotion occurs automatically.
The deterministic runner remains available for explicit exports:
session preview|merge|ir|compile --input <session.jsonl>
Use it for replay, headless automation, source hashing, redaction, validation, and cross-host merging. This optional file route must never override the interactive current-session behavior.
Return the report, approval state, generated prompt or package path, selected destination, global command, verification evidence, and blockers. A candidate is not a promotion or publication receipt.
An open-source AI agent OS inspired by OpenAI Dots, Meta Muse, Claude Duet, Nous Hermes, and Mem0. Built to lead entire projects rather than isolated prompts. Model-agnostic (BYOM) and native to Claude Code, Codex, Cursor, Antigravity, and Agentlas Desktop.
Use when creating a single Agentlas agent, creating a multi-agent team, or packaging an existing local/external agent into…
Use when converting, repairing, or packaging an existing local or external agent/team into Agentlas architecture for local…
Use when generating a single installable agent that should keep learning, track sources, refresh research, propose repairs, or…
Use when generating or auditing a multi-role agent team package with orchestrator, PM Soul, Memory Curator, Policy Gate, workers,…
Agentlas 시스템 운용 절차 — hep-network 편성, cargo/Agent Cloud·marketplace 활용, workforce 로스터 재사용, 메모리 계약. One(개인 에이전트)이 Agentlas를 조작할 때 이…
Use when the user types /agentlas-build, /agentlas build, or /hep-build to design, build, and package a single agent or…
Use your assigned AgentMail inbox to read email tasks, explicitly send or reply, and check delivery. Provided automatically by…
Create a new Architecture Decision Record with sequential numbering and AgentDB registration