jamesob
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local-llm
A comprehensive guide for building and configuring a high-end local machine to run state-of-the-art LLMs, with detailed hardware choices, BIOS tuning, and Docker-based model serving.
AI repository intelligence
FR-AI / ANALYSISWhy it is worth attention
It directly addresses the growing mental health burden on open source maintainers caused by poorly written AI agent messages, offering a practical, community-driven standard.
Who it is for
- AI agent developers and operators
- Open source maintainers tired of agent noise
- Project owners who want to set etiquette for agents in their repos
- Harness users (Claude Code, pi, OpenClaw) who dispatch agents
Use cases
- Preventing an agent from posting a comment or PR without first considering human impact
- Embedding disclosure rules into AGENTS.md or issue/PR templates
- Loading the skill before an autonomous agent writes anything in a repository
Strengths
- Clear, non-negotiable rules (never pretend to be human, use pronouns, be brief)
- Compatible with the Agent Skills standard, installable via CLI or git clone
- Includes fallback instructions for agents that don't reliably read full skill files
Considerations
- Models do not reliably read skills before composing text, so additional prompting or a system prompt injection is often needed
- Adoption is voluntary; its impact depends on agent operators choosing to install or follow it
- The skill itself lacks an evaluation of how well models comply after loading it
README quick start
empathy
[![skills.sh][skills-src]][skills-href]
This is a skill that helps AI agents talk to humans.
Every day, I read issues, PRs and comments written by agents. And I'm not unique. This is taking a toll on the mental health of maintainers across the whole ecosystem.
Personally, I think agents should not get between people. Human-to-human interaction is precious, and it's what makes open source a delight. My rules for using AI in open source specifically exclude LLM-written comments and PR descriptions, for that reason.
But I realise not everyone agrees with me.
So this skill exists as an experiment. I want to see if it's possible to tackle the way that agents tend to relate to open source maintainers. Before an agent posts anything a human will read, it should ask:
- How will this person feel when they read this?
- Would they want to receive it at all?
- Do they know they're talking to an agent?
- Am I giving them something, or just taking their attention?
Plus some instructions I consider non-negotiable:
- Never pretend to be human.
- Use people's pronouns.
- Be brief.
- Sometimes the kindest thing is not to post.
[!NOTE] I used an LLM to generate the text of the skill ... but not this README.
Install
This follows the Agent Skills standard, so it works with any compatible harness.
With the skills CLI:
npx skills add danielroe/empathy
Or clone it into your harness's skills directory:
# Claude Code
git clone https://github.com/danielroe/empathy ~/.claude/skills/empathy
# pi
git clone https://github.com/danielroe/empathy ~/.pi/agent/skills/empathy
# OpenClaw
git clone https://github.com/danielroe/empathy ~/.openclaw/skills/empathy
The skill content lives in SKILL.md.
Making sure it actually loads
Models don't reliably read skills before composing text, so the skill's description embeds the minimum rules so they're always in context.
For autonomous agents please consider forcing the full skill:
- say "read the empathy skill before posting anything a human will read" in your dispatch prompt
- or invoke it directly (
/skill:empathyin pi) - or append
SKILL.mdto the agent's system prompt
For maintainers
If you don't want to i
Description
A skill that helps AI agents talk to humans.
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