research — agentops research, llmops-demo-ts, community, agentops, ide skills, langgraph, langgraph-js, llmops, typescript, Claude Code, Cursor

v1.0.0

このスキルについて

Demonstrate LLMOps in TypeScript

# Core Topics

yu-iskw yu-iskw
[6]
[4]
Updated: 4/6/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 1/11

This page remains useful for operators, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Review Score
1/11
Quality Score
49
Canonical Locale
en
Detected Body Locale
en

Demonstrate LLMOps in TypeScript

このスキルを使用する理由

Demonstrate LLMOps in TypeScript

おすすめ

Suitable for operator workflows that need explicit guardrails before installation and execution.

実現可能なユースケース for research

! セキュリティと制限

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.
  • - The page lacks a strong recommendation layer.
  • - The page lacks concrete use-case guidance.
  • - The page lacks explicit limitations or caution signals.
  • - The underlying skill quality score is below the review floor.

Source Boundary

The section below is supporting source material from the upstream repository. Use the Killer-Skills review above as the primary decision layer.

Labs Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is research?

Demonstrate LLMOps in TypeScript

How do I install research?

Run the command: npx killer-skills add yu-iskw/llmops-demo-ts/research. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

Which IDEs are compatible with research?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add yu-iskw/llmops-demo-ts/research. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use research immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Imported Repository Instructions

The section below is supporting source material from the upstream repository. Use the Killer-Skills review above as the primary decision layer.

Supporting Evidence

research

Install research, an AI agent skill for AI agent workflows and automation. Works with Claude Code, Cursor, and Windsurf with one-command setup.

SKILL.md
Readonly
Imported Repository Instructions
The section below is supporting source material from the upstream repository. Use the Killer-Skills review above as the primary decision layer.
Supporting Evidence

Research

Research the following topic and produce a structured report:

$ARGUMENTS

Instructions

  1. Search for authoritative sources: Use WebSearch to find official documentation, GitHub repos, and specifications
  2. Read and verify: Use WebFetch to read documentation pages, cross-reference multiple sources
  3. Check local context: Use Grep and Read to understand how the topic relates to the current codebase
  4. Produce a structured report with findings, sources, and actionable recommendations

Output Format

text
1## Research Report: [Topic] 2 3### Summary 4[2-3 sentence overview] 5 6### Key Findings 71. **[Finding]** 8 - Detail: [What was learned] 9 - Source: [URL] 10 - Relevance: [How this applies to our project] 11 12### Recommendations 13- [Actionable items based on findings] 14 15### Sources 16- [URL]: [Description]

Rules

  • Always include source URLs for every claim
  • Prefer official documentation over blog posts
  • Check that documentation matches the library versions in our project
  • Note any uncertainties or conflicting information
  • Focus on what's relevant — skip tangential details

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