Modify or debug s6 services in the OpenAmer Docker image.
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Modify or debug s6 services in the OpenAmer Docker image.
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Recover from a failed or broken `openamer update`.
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Plan and prepare an OpenAmer-specific fine-tune from the collected brain data: data curation, ChatML JSONL, training, evaluation. 'The organism becomes its own brain'.
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Train an OpenAmer-specific small model from the collected brain data (QLoRA on NVIDIA, CPU smoke-test on laptop). 'The organism becomes its own brain' — build a fine-tune dataset, train, eval, export.
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Use, configure, theme, extend, and orchestrate OpenAmer Agent.
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Use when the agent needs recursive reasoning, episodic memory retrieval, internet learning, or world-model prediction. Mini-OpenAmer: the 2B hybrid Mamba core with 9 tools, running 24/7 on Damir's laptop.
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Use for A/B experiments on OpenAmer configs and skills.
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Use when modifying OpenAmer's own core code safely. Gate every change behind the test suite with automatic rollback.
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Sync skills/cron/config between OpenAmer profiles.
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Write a markdown plan to .openamer/plans/; no execution.
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Configure and troubleshoot Honcho memory for OpenAmer.
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Use for OpenAmer central CLI Commander with 28 subcommands.
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Author in-repo SKILL.md files: frontmatter and structure.
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Use for the Windows TTS+STT voice interface in OpenAmer.
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Use for API-key health checks, rotation, and monitoring.
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Use when setting up OpenAmer auto-backup.
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Run and grow the OpenAmer Agent-to-Agent swarm: identity, trust, node-to-node ask, signed skill/insight sharing, and the autonomous self-learning loop.
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Vollständige Dokumentation des OpenAmer Plugin-API-Systems. Hooks, Events, Lifecycle, manifest.json Format, Config-Integration und Plugin-Manager.
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Import an OpenClaw setup (memories, skills) into OpenAmer.
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Limited context lengths makes perpetual chat challenging MemGPT manages a virtual context (inspired
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While next token prediction is an effective training objective, it imposes a fundamental constraint on the LLM as a reasoning machine: the explicit re
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View in article Table 3 Comparative analysis of selected machine learning models for stock predictio
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Previous Next Close the short story Stay in the loop, with exclusive offers and product previews.
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Engineers who want an agent to autonomously plan, edit across files and run tests on complex real-wo
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