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AI Agent Workflow Collection

Skill pack
5 skills0 selected
xberg-ioSkills in this pack

Extract keywords from documents using YAKE algorithm with support for 34 languages (Arabic to Chinese).

English

Use when a static fetch returns nothing useful and the page needs a real browser. Covers --browser-mode auto|always|never, external CDP via --browser-endpoint, symptoms of JS-only pages and WAF blocks, and the performance cost.

English

Use when running the liter-llm api OpenAI-compatible gateway — virtual keys, per-key rate limits, budgets, cost tracking, and model routing. Covers the TOML config and the 22 REST endpoints.

English

Use when streaming tokens incrementally from an LLM via liter-llm over SSE or async iterators. Covers chatstream, delta handling, and null-content chunks.

English

Use when defining functions/tools for an LLM to call through liter-llm, or requesting structured JSON outputs. Covers tool schemas, toolcalls handling, and response formats.

English

Includes Extracting Keywords, Headless Fallback, Running the Proxy, and other workflows.

Install with
Claude CodeCodexCursorGitHub CopilotGemini CLI

Supported by the Atlas install prompt. Skill-specific requirements vary.

Pack stats

Skills5CategorygeneralStars0

What’s included

Extracting Keywords

Extract keywords from documents using YAKE algorithm with support for 34 languages (Arabic to Chinese). Use when users request keyword extraction, key terms, topic identi

Headless Fallback

Use when a static fetch returns nothing useful and the page needs a real browser. Covers --browser-mode auto|always|never, external CDP via --browser-endpoint, symptoms of JS-only pages and WAF blocks, and the performance cost.

Running the Proxy

Use when running the liter-llm api OpenAI-compatible gateway — virtual keys, per-key rate limits, budgets, cost tracking, and model routing. Covers the TOML config and the 22 REST endpoints.

Streaming Responses

Use when streaming tokens incrementally from an LLM via liter-llm over SSE or async iterators. Covers chatstream, delta handling, and null-content chunks.

Tool Calling

Use when defining functions/tools for an LLM to call through liter-llm, or requesting structured JSON outputs. Covers tool schemas, toolcalls handling, and response formats.

Quick start

  1. Choose your skills. Select individual skills above, or choose the entire pack.
  2. Copy the install prompt. Use Copy install prompt above the list.
  3. Send it to your agent. Paste into your coding agent’s chat. Your agent reviews the source and guides the setup.

Try it with your agent

After installation, start with a request like:

Example request
Use the Extracting Keywords skill to help with my task.
Ask me for the context you need before getting started.

Requirements & license

  • A coding agent that can access your project files and install skills.
  • Your agent checks each skill’s instructions, dependencies, and permissions during setup.
  • Reported license for the skills shown: MIT. The author’s terms apply.