sandbase-harness
sandbaseai
Local-first AI agent runtime with sandboxed sessions, MCP tools, memory, credentials, audit/replay, and a built-in console. Run OpenAI, Anthropic, MiniMax, DeepSeek V4, and OpenAI-compatible models on your infrastructure.
GITHUB TOPIC
16projects include this topic
The "agent-observability" topic on GitHub groups 16 open-source projects in the DeepSeek Harness (DSH) ecosystem, led by sandbase-harness with 634 GitHub stars. sandbase-harness — Local-first AI agent runtime with sandboxed sessions, MCP tools, memory, credentials, audit/replay, and a built-in console. Every project here is indexed by DSH Universe with live GitHub data — stars, activity and install status — so you can compare and install directly.
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Exact GitHub Topic match
sandbaseai
Local-first AI agent runtime with sandboxed sessions, MCP tools, memory, credentials, audit/replay, and a built-in console. Run OpenAI, Anthropic, MiniMax, DeepSeek V4, and OpenAI-compatible models on your infrastructure.
lamost423
DeepSeek Harness's execution maze—see how Agent actually works: maze timeline · data tracks · deterministic execution analysis · multi-session comparison | The execution maze for DSH agents: maze timeline, per-step data tracks, deterministic execution analysis, multi-session comparison. Formerly dsh-trace-compare.
loongsuite
OpenTelemetry tracing for DeepSeek Harness (dsh): turns each agent turn into a GenAI span tree — steps, LLM calls with TTFT, tool executions, token usage — exported over standard OTLP to Jaeger, Grafana Tempo, SigNoz, Langfuse, or any compatible backend.
TencentCloud
tencentcloud-agentobs-sdk-dsh is a DeepSeek Harness (DSH) observability plugin that reports GenAI trace data directly to Tencent Cloud Log Service (CLS). It observes DSH-native session, agent loop, LLM stream and tool lifecycles, converting them into the 5-layer span hierarchy model of the Tencent Cloud AI Agent observability spec (entry → agent → step → chat → tool), and reports directly to CLS via tencentcloud-cls-sdk-js, with no extra OTLP collector or sidecar deployment.
guhanfei-ai
Let DSH help you enrich observability of the physical world
Liu-Bot24
DeepSeek Harness (DSH) read-only execution trace review plugin: rule-based analysis, independent model interpretation, evidence location, task overview and run comparison.
bwndlct
Session execution analytics and audit reports for DeepSeek Harness — see how your agent actually worked
aa2246740
Read-only Agent work-path observer for DeepSeek Harness
forrestsweet
DeepSeek Harness session replay and redacted sharing plugin: export real Agent trajectories as standalone interactive HTML for docs, demos and issue reports.
tbxy09
Controlled request-surface replay and regression workbench for DeepSeek Harness
zhan-tz
DSH plugin: Jupyter-style living notebook — a turn-replayable dataflow DAG with git commit provenance nodes, sub-agent handoff edges, persistent ledger, hover-to-rerun and LLM explanations
bluefateludi
Local JSONL run tracing plugin for DeepSeek Harness — records agent runs, model steps, tool calls, timings, outcomes, and token usage.
dsh-plugin-evaluation
DSH plugin for agent observability and security evaluation
litefuse
DeepSeek Harness Litefuse Plugin for Agent Observability and Evals
Oscar-Williams
Know when your DeepSeek Harness tasks need you. Local alerts, quiet notifications, and a task inbox.
Mission Control dashboard and human-review workflow for DeepSeek Harness sessions, turns, and tool activity.