long-running-task-management
Breaks multi-hour tasks into checkpointed stages with resume capability. Use when a task is expected to take more than 30 minutes or multiple sessions.
git clone --depth 1 https://github.com/ArchieIndian/openclaw-superpowers /tmp/long-running-task-management && cp -r /tmp/long-running-task-management/skills/openclaw-native/long-running-task-management ~/.claude/skills/long-running-task-managementSKILL.md
# Long-Running Task Management State file: `~/.openclaw/skill-state/long-running-task-management/state.yaml` ## When to Use - Task estimated at more than 30 minutes - Task will span multiple sessions - Task modifies many files across multiple directories ## Starting a Task 1. Write initial state to the state file: - `task_id`: short kebab-case name - `status: in_progress` - `description`: one-sentence goal - `stages`: ordered list with `status: pending` for each - `started_at`: current timestamp 2. Begin the first stage ## At Each Checkpoint 1. Complete the stage 2. Run tests/verification 3. Update state file: mark stage `status: complete`, write `checkpoint` (what's stable now), write `next_action` (first thing to do on resume), update `last_updated` 4. Commit progress to git if applicable ## Resume After Interruption 1. Read the state file 2. Check `status` and `next_action` 3. Continue from the next `pending` stage — do NOT start over ## Completion 1. Update state: `status: complete`, final `checkpoint` 2. Run full verification ## Cron Wakeup Behavior On each 15-minute wakeup: - Read state file - If `status: in_progress` and `last_updated` is stale (>30 min ago): log a checkpoint update to daily memory - If `status: complete` or no active task: skip
Syncs agent daily memory and MEMORY.md to an Obsidian vault so notes are human-browsable. Use nightly or on demand.
Structured ideation before any implementation. Use when starting any non-trivial task.
Scaffolds and validates new superpowers skills. Use when creating a new skill for this repository.
Executes plans task-by-task with verification. Use when implementing a plan.
Triggers a secondary verification pass for any agent output containing factual claims, numbers, dates, or named entities before the output is acted on
Crawls a new codebase to infer stack, conventions, and key invariants, then generates a PROJECT.md context file for the agent
Handles PR review feedback by fetching comments, grouping issues, fixing one group at a time, and verifying before replies.
Detects skill name shadowing and description-overlap conflicts that cause OpenClaw to trigger the wrong skill or silently ignore one when two skills compete for the same intent.