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Adds an Autoresearch-inspired workflow that runs on a schedule to autonomously improve a target artifact toward a measurable goal. Each iteration proposes a change, evaluates it against a metric, and keeps only improvements (ratchet pattern). Includes a template program.md with a setup guard sentinel that prevents the workflow from running until the user configures their optimization goal, target files, and evaluation command. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Programs now live in .github/autoloop/programs/ (one .md file per loop) - Each program gets its own namespace: metrics, memory, branches, PRs, experiment log - Programs can specify per-program schedule and timeout via YAML frontmatter - Slash command supports program targeting: /autoloop training: try X - Template moved to programs/example.md with instructions to rename Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The pre-step runs in Python before the agent starts and checks: - Which programs are due based on per-program schedule + last_run - Which are unconfigured (sentinel/placeholders still present) - Which are paused or plateaued (5+ consecutive rejections) If no programs are due, the workflow exits with no agent invocation. This avoids burning agent compute on schedule ticks where nothing needs to happen. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The gh-aw compiler doesn't allow github.ref_name. Replace with a generic instruction to use the default branch in the edit URL. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Since add-wizard only installs the workflow .md file and can't copy companion files, the pre-step now creates .github/autoloop/programs/ and writes the template example.md on first run if the directory doesn't exist. Commits and pushes the template so the user can find and edit it in their repo. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
repo-memory is only available inside the agent runtime, not during the bash pre-step. Split persistence into two layers: 1. .github/autoloop/state.json (committed to repo) — lightweight state the pre-step reads: last_run, best_metric, pause flags, recent_statuses for plateau detection 2. repo-memory (agent only) — full iteration history, rejected approaches, detailed notes The agent updates and commits state.json at the end of every iteration so the pre-step can make scheduling decisions cheaply. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The gh-aw compiler treats backticks as reserved characters. Use chr(96) to construct them at runtime in the Python pre-step so they don't appear as literals in the workflow source. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Summary
/loopprogram.mdthat users must configure before the loop activates (setup guard via<!-- AUTOLOOP:UNCONFIGURED -->sentinel)Files added
workflows/autoloop.md— workflow definitionworkflows/autoloop/program.md— installable template for user configurationdocs/autoloop.md— documentationREADME.md— added to Research, Status & Planning sectionTest plan
gh aw compilesucceeds with the new workflowgh aw add-wizardand confirm templateprogram.mdis copiedprogram.md— should create a setup issue and exitprogram.md, remove sentinel, run — should execute an iteration🤖 Generated with Claude Code