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AI-research-feedback Skill

AI Agent SkillCode & Developer ToolsOpen source

AI-research-feedback is a Python AI agent skill. A collection of Claude Code skills for academic research review. These tools were developed by Claes Bäckman.

What is AI-research-feedback Skill?

AI-research-feedback is a Python AI agent skill. A collection of Claude Code skills for academic research review. These tools were developed by Claes Bäckman. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.

Trust signal
75/100
Maintenance signal
95/100
Adoption signal
66/100

Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement.

Key capabilities

  • Reusable instructions support
  • Includes SKILL.md support
  • Shell commands support
  • Presentation work support
  • Document generation support
  • Anthropic provider support
  • Skills/review-grant/SKILL.md config support

Available tools

Read

Technical details

SSE
  • Built for Python
  • Uses SSE transport
  • API key required

Requirements and access

PythonMIT licenseAPI key requiredAPI key required

Security and permissions

Review permissions before connecting any MCP server to an agent. Pay special attention to whether it can read local files, write data, call external services, or perform destructive actions.

Destructive actionsWrite actionsCredentials requiredCan write or update dataMay support destructive actionsAPI key required authentication

When to use AI-research-feedback Skill

  • Use it for reusing agent instructions, scripts, and references.
  • Use it for agent skills workflows.
  • Use it for coding workflows.
  • Use it for data workflows.

Built with

PythonSSE

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Frequently asked questions

What is AI-research-feedback?

AI-research-feedback is a Python AI agent skill. A collection of Claude Code skills for academic research review. These tools were developed by Claes Bäckman.

Who is AI-research-feedback best for?

AI-research-feedback is best for reusing agent instructions, scripts, and references, agent skills workflows, coding workflows, data workflows.

How do I install AI-research-feedback?

Check the AI-research-feedback GitHub repository for installation instructions.

Is AI-research-feedback actively maintained?

AI-research-feedback may need a closer maintenance check before production use.

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