scale-aiScale AI integration. Manage Organizations, Users, Goals. Use when the user wants to interact with Scale AI data.
Install via ClawdBot CLI:
clawdbot install membranedev/scale-aiGrade Limited — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Calls external URL not in known-safe list
https://getmembrane.comAudited Apr 18, 2026 · audit v1.0
Generated Apr 29, 2026
Automate the creation and management of labeled datasets using Scale AI's project and dataset APIs. This is ideal for companies needing to regularly refresh training data for computer vision or NLP models.
Manage team members within a Scale AI organization, including adding, removing, and updating user roles. Useful for enterprises that need to control access to annotation projects across departments.
Use Scale AI's annotation and model run endpoints to review and audit labeled data. This helps ensure high-quality training datasets before deploying models to production.
Leverage Membrane's proxy to call Scale AI endpoints not covered by pre-built actions, such as custom project configurations or advanced filtering. Handles authentication automatically.
Offer bundled annotation projects per month with automated dataset management and quality reviews. Revenue comes from monthly subscription fees based on data volume.
Charge per annotation task (e.g., per image or per text record) with dynamic pricing based on complexity. This model scales with customer usage.
Provide multi-user management, role-based access, and audit logs as a premium add-on. Revenue from per-user monthly fees or a flat enterprise license.
💬 Integration Tip
Start by using Membrane's pre-built actions for common tasks like user management and dataset queries. For custom endpoints, use the proxy feature to avoid manual API key handling.
Scored Apr 19, 2026
Meta-skill for AI agent self-improvement. Analyzes runtime logs to detect error patterns, regressions, and inefficiencies, then generates structured improvem...
Stop waiting for prompts. Keep working.
Turn OpenClaw into a learning-loop agent with seeded workspace rules, skill promotion, reflective memory, and proactive maintenance.
Local Python orchestration skill: multi-agent workflows via shared blackboard file, permission gating, token budget scripts, and persistent project context....
Meta-agent skill for orchestrating complex tasks through autonomous sub-agents. Decomposes macro tasks into subtasks, spawns specialized sub-agents with dynamically generated SKILL.md files, coordinates file-based communication, consolidates results, and dissolves agents upon completion. MANDATORY TRIGGERS: orchestrate, multi-agent, decompose task, spawn agents, sub-agents, parallel agents, agent coordination, task breakdown, meta-agent, agent factory, delegate tasks
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.