context-clean-up

Captures learnings, errors, and corrections to enable continuous improvement for the agent.

Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking...

Self-reflection + Self-criticism + Self-learning + Self-organizing memory. Agent evaluates its own work, catches mistakes, and improves permanently. Use when...

Security-first skill vetting for AI agents. Use before installing any skill from ClawdHub, GitHub, or other sources. Checks for red flags, permission scope, and suspicious patterns.

Typed knowledge graph for structured agent memory and composable skills. Use when creating/querying entities (Person, Project, Task, Event, Document), linkin...

Transform AI agents from task-followers into proactive partners that anticipate needs and continuously improve. Now with WAL Protocol, Working Buffer, Autonomous Crons, and battle-tested patterns. Part of the Hal Stack 🦞

Headless browser automation CLI optimized for AI agents with accessibility tree snapshots and ref-based element selection

Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.

Use when: you want a structured audit -> options -> recommended plan to improve an OpenClaw workspace (cost, model routing, context discipline, delegation, r...

Use when: you chat across topics and want explicit boundaries to prevent topic bleed. Tags: [ISO], [SCOPE], [GLOBAL], [NOMEM], [REM]. (Memory tags are signal...

Use when: hardening OpenClaw cron/background workers (POSIX shells: bash/sh) against brittle quoting, cwd/env drift, and false pipeline failures (SIGPIPE, pi...