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Found 9 Skills
Self-improving browser automation via the auto-research loop. Iteratively runs a browsing task, reads the trace, and improves the navigation skill (strategy.md) until it reliably passes. Supports parallel runs across multiple tasks using sub-agents. Use when you want to build or improve browser automation skills for specific website tasks.
Mainstream Spot Order v1.0 — Multi-chain DEX spot trading system. 6-signal ensemble (Momentum, EMA, RSI, MACD, BB, BTC Overlay) on 15m bars, 6 built-in pairs (SOL, ETH, BTC, BNB, AVAX, DOGE), auto-research strategy optimization, per-pair data collection + backtesting + paper/live trading. onchainos CLI driven, Agentic Wallet TEE signing, zero pip dependencies.
Brev instance operating guidance for NeMo-RL agents working in /home/ubuntu/RL with limited workspace disk, a larger /ephemeral volume, and optional /home/ubuntu/RL/.env secrets. Use when running auto-research campaigns, experiments, training jobs, model or dataset downloads, shared cache-heavy commands, log-producing runs, checkpoint generation, W&B or Hugging Face authenticated workflows, or any workflow that may create large files on Brev.
Builds and improves Browserbase Agent API demos through an Autobrowse-style outer loop: run a fixed task, collect Agent messages and session logs, score the result, revise one system-prompt heuristic, and confirm convergence. Use when creating a Browserbase Agents demo or POC, optimizing an Agent system prompt, diagnosing flaky Agent runs, or applying auto-research/autobrowse to the Browserbase Agents API.
Build an interactive Deal Workspace artifact for one or more target accounts - an auto-researched account brief, a buying-group map with deal roles, per-stakeholder dossiers (priorities, talking points, likely objections, a grounded opener) mined from each person's LinkedIn activity, live deal signals, prioritized plays, and a weighted warm-intro chain map that traces every route from your team's LinkedIn connections through real named intermediaries to the decision makers, ranked by how short and strong each route is. Use this whenever someone points at a company or list of companies and wants to know who to sell to and how to get in - especially if they mention or upload LinkedIn Connections.csv exports, or say things like "who do we know at X", "map our warm intros", "who are the decision makers at X", "build a stakeholder map", "find the warmest path into X", "multithread this account", or want account research turned into something shareable with their team. Trigger it even when they only say "research this account" or "help me get a meeting at X" - the warm-path mapping is the whole point.
Autonomous NeMo-RL research agent workflow for directed hypothesis testing and open-ended discovery. Guides agents through the full experiment lifecycle: understanding recipes and environments, wiring RL or NeMo-gym runs, launching reproducible baselines and iterations, analyzing results, preserving human oversight, and using git plus TSV logs as the research ledger.
Run a single experiment iteration. Edit the target file, evaluate, keep or discard.
Automatically fetches up-to-date documentation from Context7 when users ask about libraries, frameworks, APIs, or need code examples. Triggers proactively without explicit user request.
Orchestrate parallel scientist agents for comprehensive research with AUTO mode