Results for “execution”

Evaluates LLMs across 100+ benchmarks from 18+ harnesses (MMLU, HumanEval, GSM8K, safety, VLM) with multi-backend execution. Use when needing scalable evaluation on local Docker, Slurm HPC, or cloud platforms. NVIDIA's enterprise-grade platform with container-first architecture for reproducible benchmarking.

Implements a feature phase by phase from a phased JSON or Markdown plan, with configurable unit-test and quality-gate choices per phase, token-budgeted execution, resumable state, and TDD handoff.

Autonomous GAS development skill — code, deploy, test, and fix in a self-driving loop. Uses clasp for code management, Web App + gas-run.sh for auto-deploy/execution, and gws for spreadsheet read/write. Triggers on "GAS", "Apps Script", "spreadsheet automation", "clasp", "gws sheets".

Comprehensive guide for writing and running Terraform tests. Use when creating test files (.tftest.hcl), writing test scenarios with run blocks, validating infrastructure behavior with assertions, mocking providers and data sources, testing module outputs and resource configurations, or troubleshooting Terraform test syntax and execution.

Full end-to-end Mushi Mushi integration smoke test: bug capture → AI triage → story mapping → TDD test generation → approval → execution → PDCA cycle. Use when "test mushi integration", "verify full pipeline", "mushi e2e check", "does mushi work end-to-end", "smoke test mushi", or after deploying changes.

Performs interactive dynamic malware analysis using the ANY.RUN cloud sandbox to observe real-time execution behavior, interact with malware prompts, and capture process trees, network traffic, and system changes.

E2B Desktop Sandbox with autonomous computer use — cloud Linux environments for browser automation, visual UI grounding, screenshot analysis, and shell execution. Supports Browser Use cloud sessions, Playwright integration, and LLM-driven desktop control. Use when asked about sandboxes, computer use, browser automation, E2B, desktop control, visual testing, or cloud Linux environments.

Run the full autonomous engineering pipeline end-to-end (plan, work, code review, test, commit, push, open PR, watch CI, fix CI failures until green). Use only when the user explicitly requests hands-off execution of a software task and provides a feature description; do not auto-route casual conversation here.

Trigger.dev expert for background jobs, AI workflows, and reliable async execution with excellent developer experience and TypeScript-first design. Use when "trigger.dev, trigger dev, background task, ai background job, long running task, integration task, scheduled task, trigger-dev, background-jobs, ai-workflows, typescript, integrations, async, tasks, serverless" mentioned.

Runs a pre-deployment security audit of Solidity smart contracts in a Foundry project, combining static analysis (Slither, Aderyn), symbolic execution (Mythril), and property-based testing to catch reentrancy, access-control, and arithmetic bugs before deploying to an EVM chain.

Predicts the highest-impact next action for your project by running a 5-agent meta-DAG pipeline. Gathers project signals automatically (git, recent files, port-daddy, CLAUDE.md), then runs sensemaker → decomposer → skill-selector + premortem → synthesizer. When execution is approved, convert each predicted node into a skillful node prompt using skillful-node-prompt + skillful-subagent-creator, prefer live WinDAGs visualization backed by POST /api/execute and /ws/execution/:id, and fall back to ASCII only when live visualization is unavailable. Activate on: "what should I do", "what's next", "next move", "/next-move", "where should I focus", "what's the highest impact thing right now". NOT for: creating skills, debugging one specific bug, or promising topology-specific runtime behavior the current server cannot execute.

Hybrid security auditor for OpenClaw skills, Claude/Codex skills, and app repos. Use when installing a new skill, auditing a repo before use or deploy, reviewing custom scripts, checking for prompt injection, command execution, data exfiltration, dependency risk, secrets exposure, or privilege escalation. Use as the default gatekeeper before installing any third-party skill.

Coordinate multi-agent development pipelines using shared JSON task files. Use when dispatching work across dev team agents (code-agent, test-agent, docs-agent, monitor-bot), tracking pipeline progress, or running sequential/parallel workflows. Covers project init, task assignment, status tracking, agent dispatch via sessions_send, and result collection. Supports two modes: linear (sequential pipeline) and dag (dependency graph with parallel execution).

ByteDance's open-source super agent harness — spawns parallel sub-agents, Docker sandbox execution, persistent long-term memory, modular skills (research/report/slides). Built on LangChain + LangGraph. Triggers on: 'deerflow', 'deer-flow', 'bytedance agent', 'super agent harness', 'LangGraph agent orchestration', 'multi-hour agent tasks', 'spawn sub-agents', 'agent sandbox docker', 'persistent agent memory', 'agent skills system', 'AI research orchestrator', 'long-running agent tasks', 'agent with memory', 'langgraph orchestrator', 'IM channel agent integration'.

Build WinDAGs — the orchestration platform where AI agents accumulate genuine expertise through DAGs of skillful agents. Covers DAG design, execution engines, meta-DAG architecture, skill selection, dynamic mutation, visualization, and deployment. Activate on "windags", "agent DAG", "DAG of agents", "workflow orchestration", "agent pipeline", "dynamic DAG", "meta-DAG", "build windags", "implement windags". NOT for understanding WHY decisions were made (use windags-avatar), creating individual skills (use skill-architect), or managing skill libraries (use windags-librarian).

Humanization Pipeline Orchestrator v3.1 - Multi-pass 4-layer transformation pipeline Orchestrates G5 (Auditor), G6 (Humanizer), F5 (Verifier) in sequential passes Enforces checkpoints between every pass with mandatory AskUserQuestion Supports conservative (L1-2), balanced (L1-3), balanced-fast (L1-3 merged), aggressive (L1-4) modes Rich Checkpoint v2.0: section-level scores, selective humanization, target auto-stop G5+F5 parallel execution, section-selective humanization Triggers: humanize, humanize my draft, humanize manuscript, make natural, remove AI patterns Korean triggers: 휴먼화, 자연스럽게, AI 패턴 제거

Comprehensive sales and revenue operations skill. Use when building a sales team, doing founder-led sales, hiring first sales reps, navigating enterprise deals, implementing product-led sales, designing sales compensation plans, defining ICP, mapping buyer personas, or optimizing the revenue engine (RevOps). Activates for: sales strategy, rev ops, revenue operations, sales enablement, sales compensation, ICP, ideal customer profile, buyer persona, sales process, deal execution, lead scoring, lead routing, lead lifecycle, MQL, SQL, pipeline management, CRM automation, sales qualification, BANT, MEDDIC, founder sales, enterprise sales, product-led sales, startup sales, SDR, AE, quota, ramp, commission plan.