Hive Mind 🧠

The master mind AI that controls hive of AI. The orchestrator AI that controls AIs. The HIVE MIND. The SWARM MIND.

It is also possible to connect this AI to collective human intelligence, meaning this system can communicate with humans for requirements, expertise, feedback.


Inspired by konard/problem-solving

Why Hive Mind?

Hive Mind is the most autonomous, cloud-ready AI issue solver that eliminates developer babysitting while maintaining human oversight on critical decisions.

Hive Mind is a generalist AI (mini-AGI) capable of working on a wide range of tasks - not just programming. Almost anything that can be done with files in a repository can be automated.

| Feature | What It Means For You |
| ---------------------------- | -------------------------------------------------------------------------------------------------- |
| No Babysitting | Full autonomous mode with sudo access. AI has creative freedom like a real programmer. |
| Cloud Isolation | Runs on dedicated VMs or Docker. Easy to restore if broken. |
| Full Internet + Sudo | AI can install packages, fetch docs, and configure the system as needed. |
| Pre-installed Toolchain | 25GB+ ready: 10 language runtimes, 2 theorem provers, build tools. Can install more. |
| Token Efficiency | Routine tasks automated in code, so AI tokens focus on creative problem-solving. |
| Time Freedom | What takes humans 2-8 hours, AI completes in 10-25 minutes. "The code is written while you sleep." |
| Scale with Orchestration | Parallel workers feel like a team of developers, all for ~$200/month. |
| Human Control | AI creates draft PRs - you decide what merges. Quality gates where they matter. |
| Any Device Programming | Manage AI from any device with /solve and /hive. No PC, IDE, or laptop required. |
| 100% Open Source | Unlicense (public domain). Full transparency, no vendor lock-in. |

> _"Compared to Codex for $200, this solution is fire."_ - User feedback

Cost: Claude MAX subscription (~$200/month, currently 50% off = $400 value) provides almost unlimited usage for Hive Mind - the best value/quality balance on the market.

Hive Mind has high creativity indistinguishable from average programmers. It asks questions if requirements are unclear, and you can clarify on the go via PR comments.

For detailed features and comparisons, see docs/FEATURES.md and docs/COMPARISON.md.

⚠️ WARNING

It is UNSAFE to run this software on your developer machine.

It is recommended to use SEPARATE Ubuntu 24.04 installation (installation script is prepared for you).

This software uses full autonomous mode of Claude Code, that means it is free to execute any commands it sees fit.

That means it can lead to unexpected side effects.

There is also a known issue of space leakage. So you need to make sure you are able to reinstall your virtual machine to clear space and/or any damage to the virtual machine.

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THIS SOFTWARE CANNOT GUARANTEE ANY SAFETY FOR YOUR TOKENS OR OTHER SENSITIVE DATA ON THE VIRTUAL MACHINE.

There are infinite ways to extract tokens from a virtual machine connected to the internet. This includes but is not limited to:

- Claude MAX tokens - Required for AI operations
- GitHub tokens - Required for repository access
- API keys and credentials - Any sensitive data on the system

IMPORTANT SECURITY CONSIDERATIONS:

- Running on a developer machine is ABSOLUTELY UNSAFE
- Running on a virtual machine is LESS UNSAFE but still has risks
- Even though your developer machine data isn't directly exposed, the VM still contains sensitive tokens
- Any token stored on an internet-connected system can potentially be compromised

USE THIS SOFTWARE ENTIRELY AT YOUR OWN RISK AND RESPONSIBILITY.

We strongly recommend:

- Using dedicated, isolated virtual machines
- Rotating tokens regularly
- Monitoring token usage for suspicious activity
- Never using production tokens or credentials
- Being prepared to revoke and replace all tokens used with this system

Minimum system requirements to run hive.mjs:

``
1 CPU Core
1 GB RAM
> 4 GB SWAP
50 GB disk space
`

🚀 Quick Start

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#### Using Bun (Recommended)

`bash
bun install -g @link-assistant/hive-mind
`

#### Using Node.js

`bash
npm install -g @link-assistant/hive-mind
`

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If you don't have Docker installed yet, follow these steps to install Docker Engine on Ubuntu:

`bash


Install prerequisites

sudo apt update
sudo apt install ca-certificates curl

Add Docker's official GPG key

sudo install -m 0755 -d /etc/apt/keyrings
sudo curl -fsSL https://download.docker.com/linux/ubuntu/gpg -o /etc/apt/keyrings/docker.asc
sudo chmod a+r /etc/apt/keyrings/docker.asc

Add Docker repository

sudo tee /etc/apt/sources.list.d/docker.sources <Types: deb
URIs: https://download.docker.com/linux/ubuntu
Suites: $(. /etc/os-release && echo "${UBUNTU_CODENAME:-$VERSION_CODENAME}")
Components: stable
Signed-By: /etc/apt/keyrings/docker.asc
EOF

Install Docker

sudo apt update
sudo apt install docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin

Verify installation

sudo docker run hello-world
`

For other operating systems or detailed instructions, see the official Docker documentation.

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Run the Hive Mind using Docker for safer local installation - no manual setup required:

Note: Docker is much safer for local installation and can be used to install multiple isolated instances on a server or Kubernetes cluster. For Kubernetes deployments, see the Helm chart installation section below.

`bash


Pull the latest image from Docker Hub

docker pull konard/hive-mind:latest

Run an interactive session

docker run -it konard/hive-mind:latest

IMPORTANT: Authenticate AFTER the Docker image is installed

This avoids build timeouts and allows the installation to complete successfully

Inside the container, authenticate with GitHub

gh-setup-git-identity

Authenticate with Claude

claude

Now you can use hive and solve commands

solve https://github.com/owner/repo/issues/123
`

Benefits of Docker:

- ✅ Pre-configured Ubuntu 24.04 environment
- ✅ All dependencies pre-installed
- ✅ Isolated from your host system
- ✅ Easy to run multiple instances with different GitHub accounts
- ✅ Consistent environment across different machines

See docs/DOCKER.md for advanced Docker usage.

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Deploy Hive Mind on Kubernetes using Helm:

`bash


Add the Hive Mind Helm repository

helm repo add link-assistant https://link-assistant.github.io/hive-mind
helm repo update

Install Hive Mind

helm install hive-mind link-assistant/hive-mind

Or install with custom values

helm install hive-mind link-assistant/hive-mind -f values.yaml
`

Benefits of Helm:

- ✅ Easy deployment to Kubernetes clusters
- ✅ Declarative configuration management
- ✅ Simple upgrades and rollbacks
- ✅ Production-ready with configurable resources
- ✅ Supports multiple replicas and scaling

See docs/HELM.md for detailed Helm configuration options.

Note: The Helm chart is published to ArtifactHub for easy discovery.

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1. Reset/install VPS/VDS server with fresh Ubuntu 24.04
2. Login to root user.
3. Execute main installation script

`bash
curl -fsSL -o- https://github.com/link-assistant/hive-mind/raw/refs/heads/main/scripts/ubuntu-24-server-install.sh | bash
`

Note: The installation script will NOT run gh auth login automatically. This is intentional to support Docker builds without timeouts. Authentication is performed in the next steps.

4. Login to hive user

`bash
su - hive
`

5. IMPORTANT: Authenticate with GitHub CLI AFTER installation is complete

`bash
gh-setup-git-identity
`

Note: Follow the prompts to authenticate with your GitHub account. This is required for the gh tool to work, and the system will perform all actions using this GitHub account. This step must be done AFTER the installation script completes to avoid build timeouts in Docker environments.

6. Claude Code CLI, OpenCode AI CLI, and @link-assistant/agent are preinstalled with the previous script. Now you need to make sure claude is authorized. Execute claude command, and follow all steps to authorize the local claude

`bash
claude
`

Note: Both opencode and agent come with free Grok Code Fast 1 model by default - so no authorization is required for these tools.

7. Launch the Hive Mind telegram bot:

Using Links Notation (recommended):

`
screen -R bot # Enter new screen for bot

hive-telegram-bot --configuration "
TELEGRAM_BOT_TOKEN: '849...355:AAG...rgk_YZk...aPU'
TELEGRAM_ALLOWED_CHATS:
-1002975819706
-1002861722681
TELEGRAM_HIVE_OVERRIDES:
--all-issues
--once
--skip-issues-with-prs
--attach-logs
--verbose
--no-tool-check
--auto-resume-on-limit-reset
TELEGRAM_SOLVE_OVERRIDES:
--attach-logs
--verbose
--no-tool-check
--auto-resume-on-limit-reset
TELEGRAM_BOT_VERBOSE: true
"

# Press CTRL + A + D for detach from screen
`

Using individual command-line options:

`
screen -R bot # Enter new screen for bot

hive-telegram-bot --token 849...355:AAG...rgk_YZk...aPU --allowed-chats "(
-1002975819706
-1002861722681
)" --hive-overrides "(
--all-issues
--once
--skip-issues-with-prs
--attach-logs
--verbose
--no-tool-check
--auto-resume-on-limit-reset
)" --solve-overrides "(
--attach-logs
--verbose
--no-tool-check
--auto-resume-on-limit-reset
)" --verbose

# Press CTRL + A + D for detach from screen
`

Note: You may need to register you own bot with https://t.me/BotFather to get the bot token.

#### Codex sign-in

1. Connect to your instance of VPS with Hive Mind installed, using SSH with tunnel opened

`bash
ssh -L 1455:localhost:1455 root@123.123.123.123
`

2. Start codex login oAuth server:

`bash
codex login
`

The oAuth callback server on 1455 port will be started, and the link to oAuth will be printed, copy the link.

3. Use your browser on machine where you started the tunnel from, paste there the link from codex login command, and go there using your browser. Once redirected to localhost:1455 you will see successful login page, and in codex login you will see Successfully logged in. After that codex login command will complete, and you can use codex command as usual to verify. It should also be working with --tool codex in solve and hive commands.

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`bash


Solve using maximum power

solve https://github.com/Veronika89-lang/index.html/issues/1 --auto-continue --attach-logs --verbose --model opus --auto-fork --think max

Solve GitHub issues automatically (auto-fork if no write access)

solve https://github.com/owner/repo/issues/123 --auto-fork --model sonnet

Solve issue with PR to custom branch (manual fork mode)

solve https://github.com/owner/repo/issues/123 --base-branch develop --fork

Continue working on existing PR

solve https://github.com/owner/repo/pull/456 --model opus

Resume from Claude session when limit is reached

solve https://github.com/owner/repo/issues/123 --resume session-id

Start hive orchestration (monitor and solve issues automatically)

hive https://github.com/owner/repo --monitor-tag "help wanted" --concurrency 3

Monitor all issues in organization with auto-fork

hive https://github.com/microsoft --all-issues --max-issues 10 --auto-fork

Run collaborative review process

review --repo owner/repo --pr 456

Multiple AI reviewers for consensus

./reviewers-hive.mjs --agents 3 --consensus-threshold 0.8
`

📋 Core Components

| Script | Purpose | Key Features |
| ------------------------------------------- | ----------------------------- | ------------------------------------------------------------------------ |
| solve.mjs (stable) | GitHub issue solver | Auto fork, branch creation, PR generation, resume sessions, fork support |
| hive.mjs (stable) | AI orchestration & monitoring | Multi-repo monitoring, concurrent workers, issue queue management |
| review.mjs (alpha) | Code review automation | Collaborative AI reviews, automated feedback |
| reviewers-hive.mjs (alpha / experimental) | Review team management | Multi-agent consensus, reviewer assignment |
| telegram-bot.mjs (stable) | Telegram bot interface | Remote command execution, group chat support, diagnostic tools |

> Note: For a comprehensive analysis of the "Could not process image" error in AI issue solvers, see the Case Study: Issue #597. The case study includes root cause analysis, timeline reconstruction, and evidence of GitHub's time-limited S3 URLs causing image processing failures. Separate tools for downloading GitHub issues and PRs with embedded images are being developed at gh-download-issue and gh-download-pull-request.

🔧 solve Options

`bash
solve [options]
`

Most frequently used options:

| Option | Alias | Description | Default |
| --------------- | ----- | --------------------------------------- | --------- |
| --model | -m | AI model to use (sonnet, opus, haiku) | sonnet |
| --think | | Thinking level (low, medium, high, max) | - |
| --base-branch | -b | Target branch for PR | (default) |

Other useful options:

| Option | Alias | Description | Default |
| --------------- | ----- | ------------------------------------------------ | ------- |
| --tool | | AI tool (claude, opencode, codex, agent) | claude |
| --verbose | -v | Enable verbose logging | false |
| --attach-logs | | Attach logs to PR (⚠️ may expose sensitive data) | false |
| --help | -h | Show all available options | - |

> 📖 Full options list: See docs/CONFIGURATION.md for all available options including forking, auto-continue, watch mode, and experimental features.

🔧 hive Options

`bash
hive [options]
`

Most frequently used options:

| Option | Alias | Description | Default |
| -------------- | ----- | --------------------------------------- | ------- |
| --model | -m | AI model to use (sonnet, opus, haiku) | sonnet |
| --think | | Thinking level (low, medium, high, max) | - |
| --all-issues | -a | Monitor all issues (ignore labels) | false |
| --once | | Single run (don't monitor continuously) | false |

Other useful options:

| Option | Alias | Description | Default |
| ------------------------ | ----- | ------------------------------------------------- | ------- |
| --tool | | AI tool (claude, opencode, agent) | claude |
| --concurrency | -c | Number of parallel workers | 2 |
| --skip-issues-with-prs | -s | Skip issues with existing PRs | false |
| --verbose | -v | Enable verbose logging | false |
| --attach-logs | | Attach logs to PRs (⚠️ may expose sensitive data) | false |
| --help | -h | Show all available options | - |

> 📖 Full options list: See docs/CONFIGURATION.md for all available options including project monitoring, YouTrack integration, and experimental features.

🤖 Telegram Bot

The Hive Mind includes a Telegram bot interface (SwarmMindBot) for remote command execution.

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Want to see the Hive Mind in action? Join our Telegram channel where you can execute the Hive Mind on your own issues and watch AI solve them:

Join https://t.me/hive_mind_pull_requests

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1. Get Bot Token
- Talk to @BotFather on Telegram
- Create a new bot and get your token
- Add the bot to your group chat and make it an admin

2. Configure Environment

`bash
# Copy the example configuration
cp .env.example .env

# Edit and add your bot token
echo "TELEGRAM_BOT_TOKEN=your_bot_token_here" >> .env

# Optional: Restrict to specific chats
# Get chat ID using /help command, then add:
echo "TELEGRAM_ALLOWED_CHATS=123456789,987654321" >> .env
`

3. Start the Bot

`bash
hive-telegram-bot
`

Recommended: Capture logs with tee

When running the bot for extended periods, it's recommended to capture logs to a file using tee. This ensures you can review logs later even if the terminal buffer overflows:

`bash
hive-telegram-bot 2>&1 | tee -a logs/bot-$(date +%Y%m%d).log
`

Or create a logs directory and start with automatic log rotation:

`bash
mkdir -p logs
hive-telegram-bot 2>&1 | tee -a "logs/bot-$(date +%Y%m%d-%H%M%S).log"
`

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All commands work in group chats only (not in private messages with the bot):

#### /solve - Solve GitHub Issues

`
/solve [options]

Examples:
/solve https://github.com/owner/repo/issues/123 --model sonnet
/solve https://github.com/owner/repo/issues/123 --model opus --think max
`

#### /hive - Run Hive Orchestration

`
/hive [options]

Examples:
/hive https://github.com/owner/repo
/hive https://github.com/owner/repo --all-issues --max-issues 10
/hive https://github.com/microsoft --all-issues --concurrency 3
`

#### /limits - Show Usage Limits

`
/limits

Shows:
- CPU usage and load average
- RAM usage (used vs total)
- Disk space usage
- GitHub API rate limits
- Claude usage limits (session and weekly)
`

#### /help - Get Help and Diagnostic Info

`
/help

Shows:
- Chat ID (needed for TELEGRAM_ALLOWED_CHATS)
- Chat type
- Available commands
- Usage examples
`

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- ✅ Group Chat Only: Commands work only in group chats (not private messages)
- ✅ Full Options Support: All command-line options work in Telegram
- ✅ Screen Sessions: Commands run in detached screen sessions
- ✅ Chat Restrictions: Optional whitelist of allowed chat IDs
- ✅ Diagnostic Tools: Get chat ID and configuration info

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- Only works in group chats where the bot is admin
- Optional chat ID restrictions via TELEGRAM_ALLOWED_CHATS
- Commands run as the system user running the bot
- Ensure proper authentication (gh auth login, claude-profiles)

🏗️ Architecture

The Hive Mind operates on three layers:

1. Orchestration Layer (hive.mjs) - Coordinates multiple AI agents
2. Execution Layer (solve.mjs, review.mjs) - Performs specific tasks
3. Human Interface Layer - Enables human-AI collaboration

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#### Mode 1: Issue → Pull Request Flow

`mermaid
sequenceDiagram
participant H as Human
participant GH as GitHub
participant AI as AI Agent
participant HM as Hive Mind

H->>GH: Creates Issue
Note over H,GH: Primary human input

GH->>HM: Issue Available
HM->>AI: Assigns Issue
AI->>GH: Analyzes Issue
AI->>AI: Develops Solution
AI->>GH: Creates Draft PR

Note over H,GH: Human decision point
GH->>H: Notifies PR Created
H->>GH: Reviews PR

alt Approve & Merge
H->>GH: Merges PR
GH->>HM: PR Merged
else Request Changes
H->>GH: Adds Comments
Note over H,GH: Secondary human input
GH->>HM: Comments Added
HM->>AI: Process Feedback
AI->>GH: Updates PR
else Close PR
H->>GH: Closes PR
GH->>HM: PR Closed
end
`

#### Mode 2: Pull Request → Comments Flow

`mermaid
sequenceDiagram
participant H as Human
participant GH as GitHub
participant AI as AI Agent
participant HM as Hive Mind

Note over GH: Existing PR
H->>GH: Adds Comment
Note over H,GH: Primary human input

GH->>HM: New Comment Available
HM->>AI: Processes Comment
AI->>GH: Analyzes Feedback
AI->>AI: Updates Solution
AI->>GH: Pushes Changes

Note over H,GH: Human decision point
GH->>H: Notifies Changes
H->>GH: Reviews Updates

alt Approve & Merge
H->>GH: Merges PR
GH->>HM: PR Merged
else More Changes Needed
H->>GH: Adds More Comments
Note over H,GH: Continued human input
GH->>HM: Comments Added
else Close PR
H->>GH: Closes PR
GH->>HM: PR Closed
end
`

📖 For comprehensive data flow documentation including human feedback integration points, see docs/flow.md

📊 Usage Examples

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`bash


Auto-fork and solve issue (automatic fork detection for public repos)

solve https://github.com/owner/repo/issues/123 --auto-fork --model opus

Manual fork and solve issue (works for both public and private repos)

solve https://github.com/owner/repo/issues/123 --fork --model opus

Continue work on existing PR

solve https://github.com/owner/repo/pull/456 --verbose

Solve with detailed logging and solution attachment

solve https://github.com/owner/repo/issues/123 --verbose --attach-logs

Dry run to see what would happen

solve https://github.com/owner/repo/issues/123 --dry-run
`

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`bash


Monitor single repository with specific label

hive https://github.com/owner/repo --monitor-tag "bug" --concurrency 4

Monitor all issues in an organization with auto-fork

hive https://github.com/microsoft --all-issues --max-issues 20 --once --auto-fork

Monitor user repositories with high concurrency

hive https://github.com/username --all-issues --concurrency 8 --interval 120 --auto-fork

Skip issues that already have PRs

hive https://github.com/org/repo --skip-issues-with-prs --verbose

Auto-cleanup temporary files and auto-fork if needed

hive https://github.com/org/repo --auto-cleanup --auto-fork --concurrency 5
`

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`bash


Resume when Claude hits limit

solve https://github.com/owner/repo/issues/123 --resume 657e6db1-6eb3-4a8d

Continue session interactively in Claude Code

(cd /tmp/gh-issue-solver-123456789 && claude --resume session-id)
`

🔍 Monitoring & Logging

Find resume commands in logs:

`bash
grep -E '\(cd /tmp/gh-issue-solver-[0-9]+ && claude --resume [0-9a-f-]{36}\)' hive-*.log
`

🔧 Configuration

Authentication:

- gh auth login - GitHub CLI authentication
- claude-profiles - Claude authentication profile migration to server

OpenRouter Integration:

Use OpenRouter to access 500+ AI models from 60+ providers with a single API key. See docs/OPENROUTER.md for setup instructions covering both Claude Code CLI and @link-assistant/agent.

Environment Variables & Advanced Options:

For comprehensive configuration including environment variables, timeouts, retry limits, Telegram bot settings, YouTrack integration, and all CLI options, see docs/CONFIGURATION.md.

🐛 Reporting Issues

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If you encounter issues with Hive Mind (this project), please report them on our GitHub Issues page:

- Repository: https://github.com/link-assistant/hive-mind
- Issues: https://github.com/link-assistant/hive-mind/issues

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If you encounter issues with the Claude Code CLI itself (e.g., claude command errors, installation problems, or CLI bugs), please report them to the official Claude Code repository:

- Repository: https://github.com/anthropics/claude-code
- Issues: https://github.com/anthropics/claude-code/issues

🛡️ File Size Enforcement

All documentation files are automatically checked:

`bash
find docs/ -name "*.md" -exec wc -l {} + | awk '$1 > 1000 {print "ERROR: " $2 " has " $1 " lines (max 1000)"}'
`

Server diagnostics

Identify screens that are parents of processes that eating the resources

`bash
TARGETS="62220 65988 63094 66606 1028071 4127023"

build screen PID -> session name map

declare -A NAME
while read -r id; do spid=${id%%.*}; NAME[$spid]="$id"; done \
< <(screen -ls | awk '/(Detached|Attached)/{print $1}')

check each PID's environment for STY and map back to session

for p in $TARGETS; do
sty=$(tr '\0' '\n' < /proc/$p/environ 2>/dev/null | awk -F= '$1=="STY"{print $2}')
if [ -n "$sty" ]; then
spid=${sty%%.*}
echo "$p -> ${NAME[$spid]:-$sty}"
else
echo "$p -> (no STY; not from screen or env cleared / double-forked)"
fi
done
`

Show details about the proccess

`bash
procinfo() {
local pid=$1
if [ -z "$pid" ]; then
echo "Usage: procinfo "
return 1
fi
if [ ! -d "/proc/$pid" ]; then
echo "Process $pid not found."
return 1
fi

echo "=== Process $pid ==="
# Basic process info
ps -p "$pid" -o user=,uid=,pid=,ppid=,c=,stime=,etime=,tty=,time=,cmd=

echo
# Working directory
echo "CWD: $(readlink -f /proc/$pid/cwd 2>/dev/null)"

# Executable path
echo "EXE: $(readlink -f /proc/$pid/exe 2>/dev/null)"

# Root directory of the process
echo "ROOT: $(readlink -f /proc/$pid/root 2>/dev/null)"

# Command line (full, raw)
echo "CMDLINE:"
tr '\0' ' ' < /proc/$pid/cmdline 2>/dev/null
echo

# Environment variables
echo
echo "ENVIRONMENT (key=value):"
tr '\0' '\n' < /proc/$pid/environ 2>/dev/null | head -n 20

# Open files (first few)
echo
echo "OPEN FILES:"
ls -l /proc/$pid/fd 2>/dev/null | head -n 10

# Child processes
echo
echo "CHILDREN:"
ps --ppid "$pid" -o pid=,cmd= 2>/dev/null
}
procinfo 62220
`

Maintenance

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`
sudo reboot
`

That will remove all dangling unused proccesses and screens, which will in turn free the RAM and reduce CPU load. Also reboot may clear all temporary files, so next step can do nothing if reboot was done.

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`
df -h

rm -rf /tmp

df -h
`

These commands should be executed under hive user. If you have accidentally removed the /tmp folder itself under root user, you will need to restore it like this:

`bash
sudo mkdir -p /tmp
sudo chown root:root /tmp
sudo chmod 1777 /tmp
`

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`bash


close all (Attached or Detached) sessions

screen -ls | awk '/(Detached|Attached)/{print $1}' \
| while read s; do screen -S "$s" -X quit; done

remove any zombie sockets

screen -wipe

verify

screen -ls
``

That can be done, but not recommended as reboot have better effect.

📄 License

Unlicense License - see LICENSE

🏆 Best Practices

Hive Mind works even better when repositories have strong CI/CD pipelines. See BEST-PRACTICES.md for recommended configurations that maximize AI solver quality.

Key benefits of proper CI/CD:

- AI solvers iterate until all checks pass
- Consistent quality regardless of human/AI team composition
- File size limits ensure code is readable by both AI and humans

Ready-to-use templates are available for JavaScript, Rust, Python, Go, C#, and Java.

🤖 Contributing

This project uses AI-driven development. See CONTRIBUTING.md for human-AI collaboration guidelines.