self-learning-ai-agent

AWS service troubleshooting patterns. Use for EC2, ECS, Lambda, CloudWatch, RDS issues.

Search and read Confluence documentation. Use when looking for internal docs, knowledge base articles, runbooks, or team documentation stored in Confluence.

PostgreSQL database inspection and queries. Use when investigating table schemas, running queries, checking locks, replication status, or long-running queries.

Correlate incidents with recent deployments and code changes. Use when investigating if a deployment caused an issue, finding what changed, or identifying the commit that introduced a bug.

GitHub code search, file reading, PR review, branch/file management, and commit operations. Use when you need to search code patterns, read repository files, review pull requests, create branches, commit files, or open PRs.

Kubernetes debugging methodology and scripts. Use for pod crashes, CrashLoopBackOff, OOMKilled, deployment issues, resource problems, or container failures.

Jira issue tracking and project management. Use for creating, searching, updating, and commenting on Jira issues. Supports JQL queries for advanced searching.

Linear issue tracking and project management. Use for creating issues, searching issues, getting issue details, and managing tasks in Linear.

Notion page search and reading. Use when searching for documentation, notes, or knowledge stored in Notion workspaces.

Log, metric, and trace analysis methodology. Use when analyzing logs, investigating errors, querying metrics, or debugging production issues.

Slack integration for team communication. Use when searching for context in channels, reading channel history, posting messages, or finding discussions about topics.

Replace OpenClaw's flat-file memory with a self-learning knowledge engine featuring RAPTOR trees, knowledge graphs, conflict resolution, and importance scoring. Your agent actually gets smarter over time.