managed-agents
Local-first, self-hosted AI agent runtime with Claude Managed Agents-style APIs, sandboxed sessions, memory, tools, audit, replay, and a local Console.
40 results
Local-first, self-hosted AI agent runtime with Claude Managed Agents-style APIs, sandboxed sessions, memory, tools, audit, replay, and a local Console.
Session replay, fork-tree, audit & compare visualization for DeepSeek Harness — time machine for your agent sessions
Replay a DeepSeek Harness session at its original token cadence — an in-app playback theater with play/pause/step/speed/seek.
Persist and replay dynamic Cordis plugins: export the current Session's dynamic plugins to a fixed directory, then selectively load them back after a restart — and browse/import them from a Web Settings panel.
Weak-network adaptor for the DeepSeek Harness: transparent long-backoff model-stream retries (10-min cap), local response replay cache, heartbeat auto-reconnect, degraded-mode token economy, and a bilingual (zh/en) settings page. / 弱网适配插件:模型流长退避重试、本地响应缓存、心跳自动重连(默认 10 分钟封顶)、降级省 token、双语设置页。
Host-neutral durable DAG workflows for Agents, Tools, Skills, MCP, triggers, replay, and visual Canvas
Microsoft SkillOpt-Sleep integration for DeepSeek Harness: give your dsh agent a nightly sleep cycle that harvests past sessions, replays recurring tasks, and consolidates validated skills behind a held-out gate.
Session insights and one-click shareable HTML replay for DeepSeek Harness (DSH) · DeepSeek Harness 会话洞察与一键分享插件
Record & Replay for the dsh web GUI: (1) replay every automatically recorded session as a readable timeline, export/import shareable replay packs, re-run a recorded conversation; (2) Codex-style screen recording -> skill generation - record a computer-use session in the browser (getDisplayMedia -> webm + sampled frames), replay it, and have an agent analyze the frames and install a generated SKILL.md into ~/.dsh/skills. Hot-pluggable - mounted via the profile patch layer, no dsh source changes.
The LLM debug console inside DeepSeek Harness — capture every model call, see everything, replay anything.
深海事务所 (Abyss) — an operations console for DeepSeek Harness agent fleets: every agent is a character at a desk, every line comes from the durable session log, and any past case replays and reports from disk
Agentic Surface Compaction (ASC) for DeepSeek Harness: the model decides when and what to compact, committed as durable session-log replacements with full replay, search, and degradation
Read-only, scriptable session playback for the DeepSeek Harness WebUI
Export a minimal, secret-scrubbed, replayable problem bundle for DeepSeek Harness via the /repro command.
Replay and share redacted DeepSeek Harness sessions as standalone HTML
Replay real DeepSeek Harness turns against Standard, Minimal, Anchored, or plugin candidates with frozen request-surface evidence
dsh-docker — typed, guarded container control for DSH: structured docker/compose tools, project-aware targeting, an approval gate for destructive ops, service-health context, and a replayable status-table renderer
DeepSeek Harness (dsh) plugin that exports a session as a self-contained, replayable HTML file — full transcript, faithful tool cards, and playback at the original timing.
DeepSeek Harness 叶子工具正文边界的确定性录制、完整性校验与离线回放插件
DeepSeek Harness plugin: aligns markdown tables in assistant replies right after each turn (surface-replace, replay-safe) and adds a /clear-history command that empties the model-visible conversation while keeping the append-only log.
Turn DeepSeek Harness sessions into redacted, README-ready animated demos — as a local CLI or DSH plugin.
Unified DSH checkpoints with linked-worktree rollback, session replay, and a graphical conversation branch tree
HTTP network debugging toolset for DeepSeek Harness (dsh): a general-purpose HTTP client with SSRF/private-network protection, per-session request history with replay, response inspection, and a zero-dependency CLI.
DSH plugin: record terminal/tool output as asciinema v2 (.cast), replay with an offline embedded player, and export HTML.