plan-interview

Self-improvement skill that captures learnings, errors, and corrections to enable continuous improvement by logging failed operations, user corrections, and discovered better approaches to markdown files for later processing

An agent skill that captures learnings and errors with hook-based activation, enabling automatic skill extraction for continuous self-improvement in CI workflows.

An agent skill that uses multi-agent teams to simplify and harden code, combining collaborative agent workflows with code quality improvement.

An agent skill focused on simplifying and hardening code by reducing complexity and improving robustness in existing codebases.

Intent-framed agent skill for structuring AI agent behavior using intent-based communication patterns.

An agent skill for querying DX Data Cloud to retrieve developer productivity metrics, DORA metrics, PR/deployment data, and engineering analytics.

CI simplification and hardening skill for streamlining and securing CI/CD pipelines. Provides patterns for reducing complexity while improving security.

Monitors context window health during multi-step agent sessions, detecting drift signals like hallucination and contradiction to ride peak context quality, then executes clean handoffs with structured state files when context degrades.

A pipeline orchestrator skill that classifies tasks and routes them through the right combination of agent skills at the right depth, tying together planning, verification, self-improvement, and quality review workflows.

A skill from a philosophy-driven AI agent collection that focuses on exploiting peak context moments through structured workflows for planning, execution, verification, and self-improvement across sessions.