Update autoloop reference to point to https://github.com/githubnext/autoloop and remove local copy (#313)

Author: Copilot

README.md

@@ -28,7 +28,7 @@ Investigate faults proactively and improve CI.
 
 ### Research, Status & Planning Workflows
 
-- [🔄 Autoloop](docs/autoloop.md) - Loop anything in your repo to continuously research, develop and maintain
+- [🔄 Autoloop](https://github.com/githubnext/autoloop) - Loop anything in your repo to continuously research, develop and maintain
 - [📚 Weekly Research](docs/weekly-research.md) - Collect research updates and industry trends
 - [📊 Weekly Issue Summary](docs/weekly-issue-summary.md) - Weekly issue activity report with trend charts and recommendations
 - [👥 Daily Repo Status](docs/daily-repo-status.md) - Assess repository activity and create status reports

docs/autoloop.md

@@ -2,181 +2,6 @@
 
 > For an overview of all available workflows, see the [main README](../README.md).
 
-**Iterative optimization agent inspired by [Autoresearch](https://github.com/karpathy/autoresearch) and Claude Code's `/loop`**
+Autoloop has moved to its own repository: **<https://github.com/githubnext/autoloop>**
 
-The [Autoloop workflow](../workflows/autoloop.md?plain=1) runs on a schedule to autonomously improve target artifacts toward measurable goals. Each iteration proposes a change, evaluates it against a metric, and keeps only improvements. Supports **multiple independent loops** in the same repository.
-
-## Installation
-
-```bash
-# Install the 'gh aw' extension
-gh extension install github/gh-aw
-
-# Add the workflow to your repository
-gh aw add-wizard githubnext/agentics/autoloop
-```
-
-This walks you through adding the workflow to your repository.
-
-## How It Works
-
-```mermaid
-graph LR
-    A[Scheduled Run] --> B[Discover Programs]
-    B --> C[For Each Program]
-    C --> D[Review History]
-    D --> E[Propose Change]
-    E --> F[Implement on Branch]
-    F --> G[Run Evaluation]
-    G --> H{Metric Improved?}
-    H -->|Yes| I[Create Draft PR]
-    H -->|No| J[Record & Reject]
-    I --> K[Update Experiment Log]
-    J --> K
-```
-
-## Getting Started
-
-When you install Autoloop, a **template program file** is added at `.github/autoloop/programs/example.md`. This template has placeholder sections you must fill in — the workflow **will not run** until you do.
-
-### Setup flow
-
-```mermaid
-graph LR
-    A[Install Workflow] --> B[Rename & Edit Program]
-    B --> C[Define Goal, Targets, Evaluation]
-    C --> D[Remove UNCONFIGURED sentinel]
-    D --> E[Commit & Push]
-    E --> F[Loop Begins]
-```
-
-1. **Install** — `gh aw add-wizard githubnext/agentics/autoloop`
-2. **Rename** — Rename `.github/autoloop/programs/example.md` to something meaningful (e.g., `training.md`, `coverage.md`). The filename becomes the program name.
-3. **Edit** — Replace the placeholders with your project's goal, target files, and evaluation command. The template includes three complete examples for inspiration.
-4. **Activate** — Remove the `<!-- AUTOLOOP:UNCONFIGURED -->` line at the top.
-5. **Compile & push** — `gh aw compile && git add . && git commit -m "Configure autoloop" && git push`
-
-If you forget to edit the template, the first scheduled run will create a GitHub issue reminding you, with a direct link to edit the file.
-
-### Adding more loops
-
-To run multiple optimization loops in parallel, just add more `.md` files to `.github/autoloop/programs/`:
-
-```
-.github/autoloop/programs/
-├── training.md      ← optimize model training loss
-├── coverage.md      ← maximize test coverage
-└── build-perf.md    ← minimize build time
-```
-
-Each program runs independently with its own metric tracking, experiment log issue, and PR namespace. Copy the template, fill it in, and push — the next scheduled run picks it up automatically.
-
-## Configuration
-
-Each program file in `.github/autoloop/programs/` has three sections:
-
-### 1. Goal — What to optimize
-
-Describe the objective in natural language. Be specific about what "better" means.
-
-### 2. Target — What files can be changed
-
-List the files the agent is allowed to modify. Everything else is off-limits.
-
-### 3. Evaluation — How to measure success
-
-Provide a command to run and a metric to extract. Specify whether higher or lower is better.
-
-### Example program file
-
-````markdown
-# Autoloop Program
-
-## Goal
-
-Optimize the training script to minimize validation loss on CIFAR-10
-within a 5-minute training budget.
-
-## Target
-
-Only modify these files:
-- `train.py`
-- `config.yaml`
-
-## Evaluation
-
-```bash
-python train.py --epochs 5 && python evaluate.py --output-json results.json
-```
-
-Metric: `validation_loss` from `results.json`. Lower is better.
-````
-
-### Customizing the Schedule
-
-Edit the workflow's `schedule` field. Examples:
-- `every 6h` — 4 times a day (default)
-- `every 1h` — hourly iterations
-- `daily` — once a day
-- `0 */2 * * *` — every 2 hours (cron syntax)
-
-After editing, run `gh aw compile` to update the workflow.
-
-Note: The schedule applies to the workflow as a whole — all programs iterate on the same schedule. To run programs at different frequencies, you can install the workflow multiple times with different schedules, each pointing to a subset of programs.
-
-## Usage
-
-### Automatic mode
-
-Once at least one configured program exists, iterations run automatically on schedule. Each run processes every configured program:
-
-1. Reads the program definition and past history
-2. Proposes a single targeted change
-3. Runs the evaluation command
-4. Accepts (creates draft PR) or rejects (logs the attempt)
-
-### Manual trigger
-
-```bash
-# Run all programs now
-gh aw run autoloop
-
-# Target a specific program
-gh aw run autoloop -- "training: try using cosine annealing"
-
-# If only one program exists, no prefix needed
-gh aw run autoloop -- "try batch size 64 instead of 32"
-```
-
-### Slash command
-
-Comment on any issue or PR:
-```
-/autoloop training: try batch size 64 instead of 32
-```
-
-## Experiment Tracking
-
-Each program gets its own monthly experiment log issue titled `[Autoloop: {program-name}] Experiment Log {YYYY-MM}`. The issue tracks:
-
-- Current best metric value
-- Full iteration history with accept/reject status
-- Links to PRs for accepted changes
-- Links to GitHub Actions runs
-
-## Human in the Loop
-
-- **Review draft PRs** — accepted improvements appear as draft PRs for human review
-- **Merge or close** — you decide which optimizations to keep
-- **Adjust programs** — edit any program file to change the goal, targets, or evaluation
-- **Add/remove loops** — add or delete files in `.github/autoloop/programs/`
-- **Steer via slash command** — use `/autoloop {program}: {instructions}` to direct experiments
-- **Pause** — disable the workflow schedule to stop all loops, or add the sentinel back to a single program file to pause just that loop
-
-## Security
-
-- Runs with read-only GitHub permissions
-- Only modifies files listed in each program's Target section
-- Never modifies evaluation scripts
-- All changes go through draft PRs requiring human approval
-- Uses "safe outputs" to constrain what the agent can create
+Please refer to that repository for the latest documentation, installation instructions, and source code.