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RepoStew

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A portable skill for GitHub discovery, issue fixes, audits and PR maintenance. SKILL.md is canonical; Python helpers use the standard library plus Git/gh.

Start

  1. Select distinct absolute skill/state/repos roots; keep the canonical checkout and configuration workspace-local. Follow cold start.
  2. Validate paths.json, Python 3.11+, Git and authenticated gh.
  3. Ask for a specific issue, repository audit, discovery scope or tracked-PR follow-up. Default: approve edits and submission separately. Explicit autonomy stays within scope.

Workflows

Work Contract
Discovery Complete queue: deduplicate all authorized sources, issues before audits, no quota
Leaf Inline dispatch: only repostew-repository, full phase-specific policy before variables; fresh leaf per repo, same-repo revisit by executor ID
Contributions Submission gates: ACCEPT / ASK_MAINTAINER / SKIP; direct regular PR when qualified, policy-compliant Draft otherwise
Audit Coverage: all tracked files/docs/locales/sites; evidence and limitations
Follow-up Maintenance: independent GitHub Notifications + Email, shared inbox, live event deduplication
Authority Maintained repos: follow scope differs from verified capability
Batched continuous iteration Batches: one repo leaf, disposable job and PR; release after validation/submission, terminal and cleanup gate before next batch
Storage Disposable jobs: release after submission, restore for edits
Shared worktrees/sweep Cleanup: exact ownership/recovery checks; broad sweeps require explicit scope

The root owns queue, SQLite state, jobs and acceptance. Leaves consume complete inline policy without rereading it. Same-repo continuation refreshes authority/job; new repositories never inherit earlier repository context. See Luna profile only when that model/effort is selected.

Boundaries

Read target rules and live issue/PR state. Reproduce and deduplicate before submitting. Keep changes small, tests honest, security private and attribution truthful. No inferred merge/close/delete/release/governance authority; dependencies/services/ permissions/API/architecture changes need approval. Report-only monitors stay read-only. Preserve dirty/unknown data and credentials. Historical contribution is not active follow.

One selected SQLite state; no implicit reset/import or old-JSON fallback. Explicit rebuild requires full pagination, backup and atomic replacement; local handling/authority cannot be reconstructed from GitHub metadata.

Commands and validation

Event-driven maintenance separates lightweight GitHub intake, claimed PR execution, six-hour reconciliation, six-hour issue discovery and daily portfolio updates. Mailbox intake remains independent. See event maintenance. Luna deployments enforce gpt-6-luna / xhigh in actual launch settings. Intake cursors mean durable queuing, never a claim that all feedback was read or handled.

Use maintenance initialization to bind the installation, plan idempotent schedules, validate/cut over and recoverably clean legacy artifacts. Reinitialization repairs tasks without resetting the inbox or duplicating schedules; scheduled executions run only their own lane.

See command index, scheduled lanes and workspace entry.

python scripts/compile_leaf_prompt.py --packet /absolute/packet.json --output /absolute/new-prompt.txt
python -m compileall -q scripts
python -m unittest discover -s tests -v

Validate skill metadata with the host validator. Keep skill and target-repository changes in separate commits.

MIT © 2026 dajiaohuang