Tools

Manages BigQuery datasets, tables and jobs with the bq and gcloud CLIs, runs SQL queries and loads data, with references for client libraries, MCP and Terraform. Google's official skill; requires a Google Cloud project.

Google's official skill library and plugin marketplace: nearly 150 skills focused on Google Cloud (GKE, BigQuery, Cloud Run, IAM and more), plus 17 product plugins pairing skills with MCP for Cloud SQL, Spanner, AlloyDB, BigQuery, GCS and others.

Google's official skill that queries account data through the Google Ads MCP server to diagnose conversion drops, falling leads and impression share lost to bids, budgets or ad rank. Needs a Google Ads account, API credentials (developer token and OAuth) and Python 3.12.

Industrial-grade open-source speech recognition toolkit from Alibaba's ModelScope, with an agent-friendly funasr command that turns audio into text, JSON or SRT subtitles in one step, with speaker diarization and timestamps. Strong on Chinese. Requires PyTorch.

AI2's tool for converting PDFs and scans to Markdown with a vision LLM, handling equations, tables, handwriting and multi-column layouts, suited to bulk digitizing papers and archives. Local runs need an NVIDIA GPU with 12GB+ VRAM; otherwise use a paid OpenAI-compatible remote endpoint.

Browser control from the browser-use team: an editable CDP connection lets agents drive the Chrome you are already using, writing missing helper functions as they go and keeping them for reuse. Also offers an MCP server. Allow remote debugging in Chrome on first use.

Context and harness engineering skills: context fundamentals, degradation diagnosis and compression, multi-agent architectures, memory systems, tool design, LLM-as-judge evaluation and self-improvement loops. Focused on principles and design patterns, not tied to any agent platform.

Context and harness engineering skills covering context compression and optimization, multi-agent architectures, memory systems, tool design and LLM-as-judge evaluation, activated automatically by task. Aimed at building production-grade agent systems.

Lets Claude Code push ML research forward unattended: literature review, topic selection, experiment deployment, cross-model review loops and paper writing through rebuttal, in 80+ skills. Codex acts as the independent reviewer by default; other model pairings work too.

Official Lark (Feishu) skill to create and edit Lark Sheets: formulas, charts and pivot tables, conditional formatting and filters, plus import and export of local Excel/CSV, for summaries, budgets and reports. Needs lark-cli on a machine with Node.js, plus app setup and authorization.

Official Lark (Feishu) skill for Lark Base: create tables, add fields, add and edit records, build views, forms and dashboards, or apply ready-made templates, good for sign-ups, asset registers and trackers. Needs lark-cli on a machine with Node.js, plus app setup and authorization.

Alibaba's open-source offline data sync tool: JSON job configs batch-sync between heterogeneous sources like MySQL, Oracle, PostgreSQL, Hive, HDFS and MaxCompute, run with python datax.py. Needs JDK 1.8+ and Python; download and unpack the official toolkit.

Semgrep's official MCP server, now part of the main semgrep repo and started with semgrep mcp: lets agents run static security scans, find issues with custom rules and inspect syntax trees. Requires the Semgrep CLI; connecting to the AppSec platform needs SEMGREP_APP_TOKEN.

Semantic multi-language static analysis: find vulnerabilities and bugs with rules that look like source code, across 30+ languages with custom rules. Scans locally by default without uploading code; cross-file analysis and Pro rules require sign-in.

Helps support teams categorize and prioritize tickets, emails or chat logs and suggest next steps; drafts replies, organizes repro steps and reminds you to redact customer data before sharing. Works with exports from Zendesk, Intercom and others or pasted chats; no account or API key needed.

Version datasets and models the way Git versions code: data lives in remote storage like S3 or GCS while versions are tracked in your Git repo. Also offers reproducible pipelines and local experiment tracking, rerunning only the steps affected by a change.

ModelScope's official training framework for LLMs and multimodal models: the swift command covers pretraining, fine-tuning, RL, inference, evaluation, quantization and deployment for 600+ text and 400+ multimodal models, with Megatron parallelism and a web UI. Usually needs a GPU.

Open-source zero-shot TTS via f5-tts_infer-cli: from a few seconds of reference audio it reads Chinese or English text in the same voice, handy for lessons and videos. Needs Python, PyTorch and FFmpeg, ideally a GPU. Pretrained models are non-commercial; get consent before cloning a voice.

Turns 18 kinds of sources, including doc sites, GitHub repos, PDFs and videos, into skill packages for Claude and other platforms, or exports RAG chunks and vector store data. Optional MCP server, and it can call a local agent like Claude Code to enrich content. Needs Python 3.10+.

Security baseline and compliance checks for AWS, Azure, GCP, Kubernetes, GitHub, M365 and more, with built-in CIS, NIST, PCI-DSS, SOC 2 and other frameworks. Generates reports or opens a local dashboard. Configure credentials for each cloud account first.

Writes precise prompts for a specific AI tool: identifies the target tool, extracts your intent, asks at most three questions if details are missing, then outputs a lean, paste-ready prompt. Covers dozens of tools including ChatGPT, Claude Code, Cursor, Midjourney and Sora.

Command-line framework for warehouse modeling and ELT transformations: write models in SQL and let dbt handle dependencies, data tests and documentation. v2 is rewritten in Rust as a single binary. Maintained by dbt Labs; needs a data warehouse connection.

Classic network discovery and security auditing tool: host discovery, port scanning, service version and OS detection, plus vulnerability checks with NSE scripts. Only scan networks you are authorized to test.

Nearly 100 skills spanning the AI research workflow: ideation and literature review, fine-tuning and post-training, distributed training, inference serving, evaluation, interpretability and paper writing, tied together by an autoresearch orchestration skill.