openclaw-superpowers

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.

Reviews whether a skill will trigger reliably, guide useful behavior, avoid overlap, and produce testable outcomes.

Validates that a skill's companion scripts declare their OS and binary dependencies correctly, and checks whether those dependencies are actually present on the current machine.

Scores a skill's description field against sample user prompts to predict whether OpenClaw will correctly trigger it — before you publish or install.

Reviews a ClawHub skill's source code for security risks before installation. Use before installing any new skill.

Parallel subagent execution for complex tasks. Use when a task has independent parallel workstreams.

4-phase root cause process before any fix. Use whenever you encounter an error.

Red-green-refactor discipline. Use when writing new functionality.

Bootstrap skill — teaches the agent how to find and invoke skills. Use when starting any new task or session.

Ensures tasks are actually done, not just attempted. Use before declaring any task complete.

Creates clear, reviewable implementation plans before executing. Use after brainstorming and before writing any code.

Detects when the agent is stuck in a loop and escapes systematically. Use when you notice repeated failures or loss of direction.

Writes a resumé card at session end so context survives channel switches — and auto-injects it as a primer at the start of any new session

Searches Reddit communities for OpenClaw pain points and feature requests, scores them by signal strength, and writes a prioritized PROPOSALS.md for you to review and act on.

Monitors memory compaction for failures and enforces a three-level fallback chain — normal, aggressive, deterministic truncation — ensuring compaction always makes forward progress.

Scans OpenClaw config directories for plaintext API keys, tokens, and secrets in unencrypted files — flags exposure risks and suggests encryption or environment variable migration.

Scores how well the current context represents the full conversation — detects information blind spots, stale summaries, and coverage gaps that cause the agent to forget critical details.