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Found 20 Skills
4-tier autonomous self-healing system for OpenClaw Gateway with persistent learning, reasoning logs, and multi-channel alerts. Features Claude Code as Level 3 emergency doctor for AI-powered diagnosis and repair.
Transform AI agents from task-followers into proactive partners that anticipate needs and continuously improve. Includes memory architecture with pre-compaction flush (so context survives when the window fills), reverse prompting (surfaces ideas you didn't know to ask for), security hardening, self-healing patterns (diagnoses and fixes its own issues), and alignment systems (stays on mission, remembers who it serves). Battle-tested patterns for agents that learn from every interaction and create value without being asked.
Transform AI agents from task-followers into proactive partners with memory architecture, reverse prompting, and self-healing patterns. Lightweight version focused on core proactive capabilities.
Specialist in self-healing data pipelines — uses air-gapped local SLMs and semantic clustering to automatically detect, classify, and fix data anomalies at scale. Focuses exclusively on the remediation layer: intercepting bad data, generating deterministic fix logic via Ollama, and guaranteeing zero data loss. Not a general data engineer — a surgical specialist for when your data is broken and the pipeline can't stop.
Hybrid fingerprint + LLM pipeline for bug classification, deduplication, and ticket generation. Normalizes CI logs, creates stable fingerprints, clusters near-duplicates, then uses LLM for severity classification and ticket writing. Includes bug reporting templates and severity/priority matrix. Use when: "bug triage," "classify bugs," "failure analysis," "auto-classify," "CI failures," "bug report," "defect template." Not for: runtime self-healing of one flaky locator — use test-reliability. Not for: designing new tests from production telemetry — use observability-driven-testing. Related: qa-metrics, qa-dashboard, ci-cd-integration, qa-project-context.
Set up Sentinel production error capture in your own Convex deployment.
Use when verifying code works — after feature work, before committing, before deploy, or any request to "verify", "check", or "make sure it works"
Self-diagnosis skill for 5dive agents. Trigger this skill whenever the user says something is broken, not working, or behaving unexpectedly — or when any tool or command exits with an error. Runs a structured health check covering auth state, service health, disk, memory, recent CLI errors, and skill integrity. Surfaces a root-cause summary so the agent can fix the problem itself instead of asking the user. Also exposes a security audit sub-command for SSH keys, open ports, auth failures, and risky file permissions.