sim-lab
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- AlicenseNot gradedqualityBmaintenanceEnables ML researchers to manage experiments across local and remote AutoDL GPU instances, including experiment creation, training launch, run polling, and report writing via Claude Code.1MIT
- AlicenseNot gradedqualityCmaintenanceEnables coordinating Claude Code and Codex on one machine by fanning out tasks to multiple agents in isolated Git worktrees, comparing results, picking a winning candidate, and handing off work between harnesses. It provides MCP stdio tools, a CLI, and a local loopback web cockpit.Apache 2.0
- AlicenseBqualityAmaintenanceLocal-first Agent OS that wraps Claude Code, Codex CLI, and other coding agents in a replayable Seed → Ledger → Runtime contract, driven by an interview → seed → execute → evaluate → evolve workflow loop.3416,680 PyPI6,172MIT
- FlicenseAqualityCmaintenanceLets you @mention a bot in a Slack channel or DM to send work to a local Claude Code session and watch it run, with live self-updating turn cards, threaded answers, progress checklists and a per-channel inbox with read cursors. It runs entirely on your machine over Slack Socket Mode—no tunnel or public IP—routes misdelivered messages to the right project, and masks credentials in anything it posts back.7-
- AlicenseNot gradedqualityCmaintenanceProvides a local, vendor-agnostic control room where coding agents can be assigned tasks, exchange scoped messages, submit claims, and have work reviewed across different models, with a voxel-world interface for inspecting sessions and evidence.4MIT
- AlicenseNot gradedqualityAmaintenanceRun dynamic, multi-agent workflow scripts — agent(), parallel(), pipeline() — over real coding agents (Claude Code and OpenAI Codex), with deterministic journaling, resume, token budgets, and git-worktree isolation.7Apache 2.0
TDQS
Scored across 12 tools
Each tool maps to a distinct resource and action: catalogue for discovery, experiment CRUD/run (list/get/run/save), campaign batching, tune for search, run inspection (list/get/compare), and plan listing/saving. run_experiment, run_campaign, and tune all execute but are cleanly separated by scope (one, several variants, parameter search).
Strong verb_noun snake_case pattern throughout (list_experiments, get_experiment, run_campaign, compare_runs, save_plan). Two outliers—catalogue and tune—lack a noun and break the pattern, but the convention is otherwise predictable and readable.
12 tools is well-scoped for a simulation lab covering discovery, experiment lifecycle, campaign execution, tuning, run inspection, and plan authoring. Every tool earns its place with no redundant surface.
Core lifecycle is covered: discover, define, run, batch, tune, inspect, and compare. Minor gaps exist—no delete for experiments/plans, no single get_plan (only list_plans), and no run cancellation—but these are workable around for most workflows.