self▌

Captures learnings, errors, and corrections to enable continuous improvement across sessions.

Log learnings and errors to markdown files for continuous improvement. Coding agents can later process these into fixes, and important learnings get promoted to project memory.

元认知自学习系统 - 基于预测编码和价值驱动的Skill自动演化。

When to use this skill:

Automated learning capture in CI pipelines that deduplicates failure patterns and proposes prevention rules. \n \n Inspects PR check results and CI failures to identify recurring patterns tracked by stable pattern_key , promoting only when recurrence thresholds are met (3+ occurrences across 2+ distinct runs within 30 days) \n Ingests learning candidates from simplify-and-harden-ci and emits machine-readable YAML output without interactive prompts, suitable for headless GitHub Actions workflows

Skill by ara.so — Daily 2026 Skills collection.

$22

4-tier autonomous self-healing system for OpenClaw Gateway with Claude Code as AI emergency doctor. \n \n Escalates through watchdog monitoring, HTTP health checks with retries, AI-powered diagnosis via Claude Code, and Discord/Telegram alerts for human intervention \n Captures persistent learning documentation (symptom to solution mappings) and reasoning logs for explainable AI decision-making \n Includes metrics dashboard for tracking recovery success rates, timing, and trends across incidents

Captures learnings, errors, and corrections to enable continuous improvement across agent tasks. \n \n Logs failures, user corrections, knowledge gaps, and API errors to structured markdown files ( .learnings/ERRORS.md , LEARNINGS.md , FEATURE_REQUESTS.md ) with consistent ID, priority, and metadata \n Supports promotion of broadly applicable learnings to project memory files ( CLAUDE.md , AGENTS.md , .github/copilot-instructions.md ) to prevent recurring mistakes \n Includes recurring pattern d

Autonomous design critique mode that adds annotations to web pages via the Agentation toolbar in a visible browser. \n \n Requires the Agentation toolbar installed on the target page and the agent-browser skill available; launches in headed mode so users watch the agent scan, hover, and annotate in real time \n Uses coordinate-based mouse events to trigger annotation dialogs (standard element clicks do not work); includes helper patterns for scrolling, bounding box lookup, and dialog interaction