Labtasker Skill
Teach Claude Code to design and operate Labtasker v2 experiment queues and Workers.
Paquete de plugins · de lcf
Resumen
Labtasker Skill es un paquete de plugins para herramientas de programación con IA publicado por lcf. Marketplaces que leemos y que lo publican: 1 (Community GitHub marketplaces). Lo vimos por primera vez el 2026-10-27 y desde entonces no hemos registrado cambios. Según nuestra pasada por los marketplaces del 2026-11-03.
Qué pide
- Se instala como paquete de plugins
Ninguno de los marketplaces que leemos publica sus herramientas ni los ajustes que pide.
Lo que declara, pide y ejecuta, completo
Instala solo plugins de desarrolladores en los que confíes. Mostramos lo que publican los marketplaces y no probamos plugins.
Funciona con
- Claude Code
Según los marketplaces que lo listan y el transporte MCP que declara, tal como lo documenta cada cliente. No probamos plugins.
Conectar
Comandos y configuraciones generados solo a partir de lo que declaran sus marketplaces. No los ejecutamos por ti ni probamos plugins.
Como plugin de Claude Code
Generado a partir de lo que declara Community GitHub marketplaces.
/plugin marketplace add luocfprime/labtasker
/plugin install labtasker-skill@labtaskerDónde está publicado
| Marketplace | Estado | Versión | Cifras | Verificado | Visto por primera vez |
|---|---|---|---|---|---|
| Marketplace de la comunidad luocfprime/labtasker (Abrir el código en GitHub) | Publicado | 2.8.0 | Forks (GitHub): 6 Estrellas (GitHub): 39 |
Sin marca |
Cada cifra es del propio marketplace y nunca se suma entre marketplaces. Un marketplace que no publica cifras no muestra ninguna: sin número no es cero.
Figura en un marketplace de la comunidad
| Marketplace | Repositorio | Estrellas (GitHub) |
|---|---|---|
| labtasker | luocfprime/labtasker | 39 |
Qué contiene el paquete
Tal como se publica en Community GitHub marketplaces.
Skills: 1
labtasker
Qué cambió
- Pasó a ser un producto que seguimos
- Community GitHub marketplaces: apareció
Plugins similares
Productos cuyos propios nombres, descripciones, herramientas y skills son los más cercanos a este por su significado, en todos los marketplaces que leemos. La cercanía se ordena solo dentro de esta lista.
-
Autonomous experiment loop — modify, test, keep/discard, repeat forever
-
lab-automation
Lab platforms, ELNs, liquid handlers and manufacturing integrations.
-
AI-powered bioprotocol optimization — generate, search, and manage lab protocols via MCP
-
Scaffold a Dokimos Experiment with dataset, task, evaluators, and reporter
-
Read and update your Vara lab experiments, runs, daily plans, references and materials.
-
Read and update your Vara lab experiments, runs, daily plans, references and materials.
-
mcp io.scispot/mcp
Turn any LLM into your lab assistant: search samples, track experiments, analyze data with AI.
-
Research graph MCP for hypotheses, goals, runs, source quality, audits, and generated maps.
-
Read and scaffold organization-scoped FlaskTrack laboratory data using MCP.
Plugins similares por marketplace
La misma pregunta a cada marketplace por separado: ¿hay allí un equivalente de este plugin?
Publicado en Claude Code: claude-plugins-community (5)
-
Autonomous experiment loop for Claude Code. Run an endless optimize-measure-keep/discard cycle on any optimization target: LLM training loss, test speed, bundle size, build time…
-
Arquestra — Scientific Computing Orchestration
AI orchestration for computational chemistry and HPC workflows.
-
Research sprint orchestrator for Claude Code. Ask a question, get a decision-ready brief — every finding is tracked as a typed claim, adversarially challenged, confidence-graded…
-
20 enterprise-grade skills for autonomous AI/ML research lab operations. Includes 10 custom gap-analysis skills (research-commander, agent-debugger, model-evaluator…
-
Autonomous experiment loops on any codebase — one file, one metric, one loop. An agent edits a constrained file, runs an eval, keeps improvements, reverts failures, and repeats…
Publicado en Claude Code: claude-plugins-official (5)
-
A suite of agent skills for the full GrowthBook feature flag and experimentation lifecycle.
-
Skills for working with Langfuse, the open-source LLM engineering platform for tracing, prompt management, and evaluation.
-
Full Domino Data Lab platform support — workspaces, jobs, model deployment, experiment tracking, GenAI tracing, Spark/Ray/Dask, and app deployment for data science teams
-
DataRobot skills for AI/ML workflows — model training, deployment, predictions, feature engineering, monitoring, explainability, data preparation, App Framework CI/CD, and…
-
Skills for tracing, evaluating, and improving AI agents with MLflow. Supports the full agent improvement loop: instrument → trace → evaluate → iterate → validate.
Publicado en Claude: knowledge-work-plugins (5)
-
Connect to preclinical research tools and databases (literature search, genomics analysis, target prioritization) to accelerate early-stage life sciences R&D
-
A suite of agent skills for the full GrowthBook feature flag and experimentation lifecycle.
-
Skills for working with Langfuse, the open-source LLM engineering platform for tracing, prompt management, and evaluation.
-
DataRobot skills for AI/ML workflows — model training, deployment, predictions, feature engineering, monitoring, explainability, data preparation, App Framework CI/CD, and…
-
AI agent skills that make SaaS products data-ready for product analytics — from codebase scan to tracking plan to working instrumentation code.
Publicado en Codex: openai-curated (openai/plugins) (5)
-
Skills for NVIDIAs ecosystem spans GPU acceleration, CUDA, AI agents, inference, robotics, Physical AI, Omniverse, and simulation. This plugin helps you understand the pieces…
-
PostHog gives your AI agent direct access to your product analytics, feature flags, experiments, error tracking, surveys, logs, and LLM analytics. Ask questions about your data…
-
Predict structures, screen molecules and proteins, and design binders.
-
Evaluate Codex skills and plugins from chat with a beginner-friendly start command, local-first reports, token budget explanations, and guided benchmarking.
-
General life-sciences research workflows with query routing, evidence synthesis, and optional parallel subagent analysis across genetics, omics, biology, chemistry, structure…
Publicado en Community GitHub marketplaces (4)
-
Autonomous experiment loop — modify, test, keep/discard, repeat forever
-
lab-automation
Lab platforms, ELNs, liquid handlers and manufacturing integrations.
-
Scaffold a Dokimos Experiment with dataset, task, evaluators, and reporter
-
claudecode-research-harness-workflow
Research Agent Harness — a controlled execution environment for reproducible empirical research agents.
Publicado en Copilot CLI: github/awesome-copilot (5)
-
Run a lightweight, role-separated AI development team with flexible tools, developer-selected models, proportionate planning, and optional QA.
-
Task Researcher and Task Planner for intermediate to expert users and large codebases - Brought to you by microsoft/edge-ai
-
Microsoft Copilot Studio YAML authoring toolkit. Create, edit, validate, and test Copilot Studio agents using YAML files.
-
See your local Copilot token usage by day, model, and session, and get tips to use it more efficiently.
-
Safe BLE diagnostics, evidence workflows, and guarded automation for AI agents.
Publicado en Copilot CLI: github/copilot-plugins (5)
-
Toolkit for building Microsoft 365 Copilot declarative agents — scaffolding, JSON manifest development, and capability configuration.
-
workiq-productivity
WorkIQ productivity skills powered by the local WorkIQ CLI — read-only insights across email, meetings, calendar, Teams, SharePoint, projects, and people.
-
workiq
Query Microsoft 365 data with natural language — emails, meetings, documents, Teams messages, and more.
-
Build Power Apps Canvas Apps using the Canvas Authoring MCP server.
-
model-apps
Build and deploy Power Apps generative pages for model-driven apps with specialist agents for planning, entity creation, and parallel code generation. Requires PAC CLI >= 2.7.0…
Publicado en Cursor: cursor/plugins (5)
-
Fan large tasks out across parallel cloud agents with planners, workers, verifiers, and structured handoffs.
-
Inspect and manage feature gates, experiments, dynamic configs, and metrics.
-
Work with PostHog from chat: query product analytics and run SQL, manage feature flags and experiments, triage error tracking issues, and review session replays, surveys, and…
-
Ask Databricks Genie questions about your workspace's data in plain language.
-
Build apps, scripts, and automations with the TypeScript SDK.
Publicado en Docker MCP Catalog (5)
-
testkube-mcp io.github.kubeshop/testkube-mcp
MCP server for Testkube - Manage test workflows, executions, and artifacts via AI assistants
-
Generate, run, debug lifescience workflows.
-
Read and score Opik traces, experiments, datasets and prompts from your AI assistant.
-
Remote MCP server for the Hackle Admin API: experiments, feature flags, remote config, messaging.
-
Analyze documents, images, videos, and audio.
Publicado en Official MCP Registry (5)
-
AI-powered bioprotocol optimization — generate, search, and manage lab protocols via MCP
-
Read and update your Vara lab experiments, runs, daily plans, references and materials.
-
Read and update your Vara lab experiments, runs, daily plans, references and materials.
-
mcp io.scispot/mcp
Turn any LLM into your lab assistant: search samples, track experiments, analyze data with AI.
-
Research graph MCP for hypotheses, goals, runs, source quality, audits, and generated maps.
Publicado en PyPI (MCP servers) (5)
-
Read and score Opik traces, experiments, datasets and prompts from your AI assistant.
-
Langfuse MCP server for accessing and analyzing telemetry data via natural language
-
220 browser automation tools for Chrome, Edge, and Firefox via CDP + BiDi. 100% Python.
-
Read, measure and explain LLM eval runs of a digline suite. Cannot promote a baseline.
-
Find & fetch research datasets across 21 archives, omics registries, and literature sources.
Publicado en npm registry (MCP servers) (5)
-
Find test gaps, generate grounded tests, and dynamically prove behavior with mutation testing.
-
Hire human data labelers, RLHF annotators, and evaluators from your coding agent.
-
Read raw lab-instrument files offline: metadata, previews, integrity checks, open-format export.
-
Run AI-moderated qualitative interviews with real people from any MCP client; cited findings.
-
140 deterministic tools for your AI: logs, tests, SQL, diagrams, SPARQL. Local, no network.
Encontrados por significado, no por código ni repositorio compartidos: los plugins similares siguen siendo productos distintos, y esto no es una reseña ni una recomendación.
¿Quieres esta marca para tu plugin en nuestro catálogo?
Demuestra que lo mantienes con un archivo en su repositorio, un archivo en tu dominio o un registro DNS, y podrás mostrar esta marca en la ficha, con banners en vivo para tu web y tu README. Cómo funciona la verificación
Además recibirás avisos cuando un marketplace lo publique, lo retire, cambie su marca verificada o lo que pide, y su endpoint remoto quedará monitorizado como un servicio web.
Datos de Community GitHub marketplaces. Las cifras proceden de nuestros propios recorridos periódicos por los marketplaces, leída por última vez el . No publicamos datos de contacto de los editores de plugins.