Loading...
Loading...
Found 9 Skills
Observe the user's screen via screenpipe, detect repeated research workflows, match them against existing academic-skills, and draft new skills (or composition recipes that chain existing ones) for the patterns not yet covered. Use when the user asks to analyze their recent work and propose skills based on what they actually do. Requires the screenpipe daemon (https://github.com/screenpipe/screenpipe) running locally on port 3030 — the skill has no other data source and will refuse to run if screenpipe is unreachable. All detection runs locally; only redacted cluster summaries reach the LLM.
Analyze workflow runs - frequency, duration, success rates, and efficiency
Compare FinOps metrics across multiple repositories in an organization
This skill should be used when recognizing recurring themes, identifying patterns in work or data, or when "pattern", "recurring", or "repeated" are mentioned. For implementation, see codify skill.
Review failed Exarchos MCP tool calls from the current session, diagnose root causes, and categorize into code bug, documentation issue, or user error. Use when the user says 'dogfood', 'review failures', 'what went wrong', 'triage errors', or runs /dogfood. Scopes exclusively to Exarchos tools (exarchos_workflow, exarchos_event, exarchos_orchestrate, exarchos_view, exarchos_sync). Do NOT use for debugging application code or non-Exarchos tool failures.
Quality review and audit for Claude Code skills. Analyzes skill structure, description quality, workflow design, token efficiency, and anti-patterns against best practices. Use when user wants to review a skill, audit a skill, check skill quality, evaluate a skill, critique a skill, lint a skill, or validate a skill. Triggers: 'review skill', 'audit skill', 'skill quality', 'check my skill', 'evaluate skill', 'skill lint', 'validate skill', 'skill review', 'is this skill good', 'improve this skill'.
Query Langfuse traces for debugging LLM calls, analyzing token usage, and investigating workflow executions. Use when debugging AI/LLM behavior, checking trace data, or analyzing observability metrics.
Agent Design Consultant and Review Tool. Based on 12-Factor AgentOps best practices, it is used for: (1) Discussing Agent architecture design solutions; (2) Reviewing the design of existing Agents/Skills/workflows, identifying issues, and providing improvement suggestions. Trigger phrases: Review my agent, Help me analyze this skill, Agent design, Agent optimization, Help me review this workflow, What's wrong with this agent, How to design an agent, Agent architecture consultation.
Perform a comprehensive session retrospective. Use when user says "retro", "retrospective", "회고", or at the end of a working session.