Tools

Turns resolved tickets, common questions or workarounds into publish-ready knowledge base articles, structured as how-to guides, troubleshooting, FAQs or known issues, and optimized for search. From Anthropic's official customer-support plugin.

Customer support plugin: triages and prioritizes tickets with routing suggestions, drafts customer replies, packages escalations, researches customer issues across sources and turns resolved issues into knowledge base articles. Official from Anthropic.

Before replying to a customer, verifies answers across the knowledge base, past tickets, CRM and chat history, grades confidence and cites sources; can also find whether an issue was reported before or what a customer was told. From Anthropic's official customer-support plugin.

For preclinical life sciences research: bundles MCP connectors for PubMed, bioRxiv, ChEMBL, Open Targets, ClinicalTrials and more, plus analysis skills for single-cell RNA QC, scvi-tools and nf-core pipelines. Official from Anthropic; some data sources need accounts.

Support persona skill for the gws CLI: triages support-labeled Gmail, turns emails into tasks, logs tickets in Google Sheets, escalates urgent issues to Chat and books follow-ups. Needs gws authorized via your own Google Cloud project plus its companion skills; not officially supported by Google.

Turns websites and Electron desktop apps into deterministic CLIs, with built-in adapters for Reddit, Hacker News, Bilibili, Zhihu, Xiaohongshu and more, and lets agents operate any page through your signed-in Chrome. Needs its companion browser extension.

For SaaS customer success teams: three standard-library Python scripts turn customer data into health scores, churn-risk tiers and ranked expansion opportunities, with reproducible results. Needs Python and customer data in the sample JSON format. Part of the claude-skills collection.

CLI and library for evaluating and red-teaming LLM apps: compare prompts and model outputs in bulk, scan for security vulnerabilities and plug into CI/CD, with evals running locally. Now part of OpenAI and still open source under MIT.

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.

Google's official skill library, focused on Google Cloud: 100+ skills for gcloud, Cloud Run, GKE, BigQuery, IAM, monitoring and logging, and the Well-Architected Framework, plus Ads and Analytics.

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.

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 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.

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.

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 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.

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.

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.

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.