Results for “wit-ai”

Scaffolds an isolated cloud development box per agent using Crabbox and Daytona, with its own database, dev server, and in-box browser for parallel testing without port or state collisions.

OpenStack Heat orchestration service skill. Use when working with HOT templates, stack lifecycle management, auto-scaling groups, nested stacks, resource type registry, template validation, or infrastructure-as-code patterns within OpenStack. Covers deployment via Kolla-Ansible, template authoring, stack operations, and troubleshooting common orchestration failures.

Drives the Rowan cloud quantum-chemistry platform via its Python API for computational chemistry — pKa prediction, geometry optimization, conformer searching, molecular property calculations, protein-ligand docking (AutoDock Vina), and AI protein cofolding (Chai-1, Boltz-1/2), with cloud compute and no local setup. Use when running DFT or semiempirical methods, neural network potentials (AIMNet2), molecular property or protein-ligand binding predictions, or automated computational chemistry pipelines. Part of the AlterLab Academic Skills suite.

Scaffold a one-command dev-local launcher for any codebase by investigating services, ports, and infra dependencies, then generating a single script with tmux session management.

Orchestrates parallel AI agent sessions using dmux, a tmux pane manager, with patterns for research, implementation, testing, and code review across multiple harnesses.

Analyzes AWS ECS clusters, services, and tasks, including health, deployment status, task failures, capacity providers, and resource utilization, with parallel execution and anti-hallucination guardrails.

Deep-dive analysis of AWS RDS instances using Performance Insights, event subscriptions, proxy health, and global database status, with parallel execution and anti-hallucination guardrails.

Manages NS1 DNS zones, records, filter chains, monitoring jobs, and traffic steering via the NS1 API, with a discovery-first workflow for inspection and troubleshooting.

Review AI agent skills using a dual-axis method: deterministic code-based checks and LLM deep review, with weighted scoring and improvement recommendations.

Builds a scheduled, AI-powered data collection agent that scrapes public sources, enriches results with Gemini Flash, and stores them in Notion, Sheets, or Supabase.

Manages Xata serverless databases via the xata CLI and REST API, covering discovery of workspaces, databases, branches, tables, schema, migrations, and record counts with read-only operations.

Build, edit, and deploy full-stack websites or web apps using the Higgsfield CLI, with two distinct product types: standalone websites or Higgsfield-integrated apps.

Analyzes AWS CloudTrail events and trails, including trail health, API activity, security investigations, resource changes, and event selector audits, with parallel execution and anti-hallucination guardrails.

Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommendation systems, or semantic search at scale. Best for serverless, managed infrastructure.

Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommendation systems, or semantic search at scale. Best for serverless, managed infrastructure.

Expert guidance for Xata, the serverless data platform that combines PostgreSQL, Elasticsearch, and AI capabilities in a single API. Helps developers build applications with full-text search, vector similarity search, file attachments, and branching — all through a type-safe TypeScript SDK.

Benchmark-relative quality gate. Scores the draft against the research dossier's beat spec (depth, consensus coverage, evidence) plus AI-tell and voice signals, runs an adversarial read armed with the SERP benchmark, and emits the verdict that gates the pipeline.

Mine LITCOIN — a proof-of-comprehension and proof-of-research cryptocurrency on Base. Use when the user wants to mine crypto with AI, earn tokens through reading comprehension or solving optimization problems, stake LITCOIN, open vaults, mint LITCREDIT, manage mining guilds, deploy autonomous agents, or interact with the LITCOIN DeFi protocol.

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

Generate tailored AI agent instruction files for VS Code Copilot and other coding agents, using AgentRC to analyze your codebase and produce flat or nested instruction files with optional per-area scoping.

Runs a three-layer verification pipeline on AI-generated output: extracts verifiable claims, finds supporting or contradicting sources via web search, and produces a structured verification report with source links for human review.

CloudBase is a full-stack development and deployment toolkit for building and launching websites, Web apps, 微信小程序 (WeChat Mini Programs), and mobile apps with backend, database, hosting, cloud functions, storage, AI capabilities, Agent, and UI guidance. This skill should be used when users ask to develop, build, create, scaffold, deploy, publish, host, launch, go live, migrate, or optimize websites, Web apps, landing pages, dashboards, admin systems, e-commerce sites, 微信小程序 (WeChat Mini Programs), 小程序, Agent, 智能体, uni-app, or native/mobile apps with CloudBase (腾讯云开发, 云开发), including authentication, login, database, NoSQL, MySQL, cloud functions, CloudRun, storage, AI models, and UI guidance, or when they ask to compare CloudBase with Supabase or migrate from Supabase to CloudBase.

Build server-side call automation workflows with Azure Communication Services Call Automation Java SDK, including IVR systems, call routing, recording, DTMF recognition, text-to-speech, and AI-powered call flows.

Authenticates and connects to Google Cloud Agent Platform for inference with Gemini and third-party OpenMaaS models (Llama, DeepSeek, Qwen). Generates code for multiple SDKs, configures endpoints, and troubleshoots common errors.

Manages persistent coding sessions across multiple AI coding engines including Claude Code, Codex, Antigravity, Cursor, and OpenCode, with support for multi-agent councils, cross-session messaging, deep planning, parallel code review, and autonomous workspace iteration.

Perform high-performance genomic interval operations and bioinformatics file I/O on Polars DataFrames, including overlap, nearest, merge, coverage, complement, subtract, and reading/writing BED, VCF, BAM, GFF, FASTA, and FASTQ formats with streaming and cloud-native support.

All-in-one fullstack dev engine. /aura: 46 modes (build/fix/clean/deploy/review/spec/lore/ax/experiment/payment/debug/qa/orchestrate/escalate+), 6-layer security with 32 hooks, tiered models (ZERO/ECO/PRO/MAX), 8 languages, 16 specialized agents, SPEC/EARS/TRUST5/XLOOP/RALF/Autopus absorbed. ~55% token savings.

Generate comprehensive clinical reports including case reports (CARE guidelines), diagnostic reports, clinical trial reports (ICH-E3, SAE, CSR), and patient documentation (SOAP, H&P, discharge summaries) with templates, regulatory compliance, and validation tools.

Layer 1a of the keyword research pipeline. Generates seed keywords (broad niche terms) and modifiers (best, how-to, vs, calculator, etc.) from brand-config so the keyword multiplier has a real foundation to expand from. Replaces the "AI gives you generic keywords" problem with the structured 10-second hero prompt.

Box API integration with managed OAuth. Manage files, folders, collaborations, and cloud storage. Use this skill when users want to upload, download, share, or organize files and folders in Box. For other third party apps, use the api-gateway skill (https://clawhub.ai/byungkyu/api-gateway). Requires network access and valid Maton API key.

Master defensive Bash scripting for production automation, CI/CD pipelines, and system utilities. Expert in safe, portable, and testable shell scripts with POSIX compliance, modern Bash 5.x features, and comprehensive error handling. Use when writing shell scripts, bash automation, CI/CD scripts, system utilities, or mentions "bash", "shell script", "automation", "defensive programming", or needs production-grade shell code.

Use CircleCI Chunk for AI-assisted CI/CD work through either the Chunk web UI or the chunk-cli. Trigger this skill when users ask to set up Chunk, troubleshoot or fix failing builds with Chunk, configure Chunk environments, schedule/proactively run Chunk tasks, or use chunk-cli commands such as init, validate, build-prompt, auth, sandbox, task, and skill install.

Build with Aurora DSQL — manage schemas, execute queries, handle migrations, diagnose query plans, and develop applications with a serverless, distributed SQL database. Covers IAM auth, multi-tenant patterns, MySQL-to-DSQL migration, DDL operations, query plan explainability, and SQL compatibility validation. Triggers on phrases like: DSQL, Aurora DSQL, create DSQL table, DSQL schema, migrate to DSQL, distributed SQL database, serverless PostgreSQL-compatible database, DSQL query plan, DSQL EXPLAIN ANALYZE, why is my DSQL query slow.

Build a fully automated AI-powered data collection agent for any public source — job boards, prices, news, GitHub, sports, anything. Scrapes on a schedule, enriches data with a free LLM (Gemini Flash), stores results in Notion/Sheets/Supabase, and learns from user feedback. Runs 100% free on GitHub Actions.

12-agent academic paper writing pipeline. 10 modes (full/plan/outline/revision/revision-coach/abstract/lit-review/format-convert/citation-check/disclosure). 6 paper types, 5 citation formats, bilingual abstracts, LaTeX/DOCX-via-Pandoc/PDF output. Style Calibration + Writing Quality Check + Anti-Patterns with IRON RULE markers. Triggers: write paper, academic paper, guide my paper, parse reviews, AI disclosure, 寫論文, 學術論文, 引導我寫論文, 審查意見.

Operate Firebase from the terminal with `firebase-tools`: install/auth the CLI, bootstrap `firebase.json` / `.firebaserc`, run the Emulator Suite, deploy Hosting / Functions / rules / App Hosting, manage preview channels, and handle Firebase admin tasks like auth import/export, Remote Config, App Distribution, and Extensions. Use when the job is Firebase platform/project operation through the CLI. Triggers on: firebase deploy, firebase init, firebase emulators, firebase hosting, firebase functions, firebase firestore, firebase database, firebase auth import, firebase remote config, firebase app distribution, firebase extensions, firebase apphosting, firebase dataconnect, firebase cli, firebase-tools, deploy firebase, firebase preview channel, firebase login, firebase use, firebase target apply. Route backend AI workflow orchestration to `genkit` and direct in-app SDK integration to `genkit` (`client-ai-logic` mode).