Own the goal lifecycle with tier classification, planning, review, and acceptance proof.
npx skills add https://github.com/rdleclerc/agentic-uber-skills --skill ubergoal
Please help me install this Agent Skill. Skill: ubergoal Source: https://github.com/rdleclerc/agentic-uber-skills/tree/main/ubergoal Command: npx skills add https://github.com/rdleclerc/agentic-uber-skills --skill ubergoal
Ubergoal removes ambiguity and missing evidence in substantial agentic coding work by making the goal owner accountable for tiering, routing, review-board coordination, acceptance proof, and post-run learning.
Use the ubergoal skill when you have substantial coding or agentic-system work that needs safe tiering, specialist review-board lanes, rigorous planning, and evidence-backed final acceptance.
High-intent search queries and answers about installing and using this skill.
Risk tiering for multi-agent coding workflows is managed by classifying tasks into operational tiers, routing Tier 2+ scenarios to specialist review-board lanes, and enforcing child-by-child execution discipline to ensure safe delivery.
Long-running agentic coding tasks are coordinated safely through a goal-owning lifecycle wrapper that handles tier classification, bounded execution, and evidence-based routing to ensure rigorous planning and final acceptance proof.
Repeated unexpected test failures trigger a failure-aware adaptation loop that stops execution, initiates root cause analysis, and applies scope correction rather than blindly patching the code.
Evidence receipts for agentic system acceptance are generated by enforcing policy-adherence checks, reporting expectation versus surprise deltas, and capturing a final Uber run receipt before allowing task completion.
Specialist review-board lanes are needed when coding lifecycle routing identifies work as Tier 2 or higher, requiring rigorous planning, multi-agent coordination, and bounded execution oversight.
Plan routing for agentic workflows can operate by creating or binding a platform goal when available, but still enforces expectation gating, planning, and acceptance proof even without a native platform integration.
saffron-healthGenerate phased specification documents from code and documentation analysis.
Pepsi1978Automate post-task retrospectives and persist learnings to MEMORY.md and rules.
uladzemerEnforce proof-based verification and root-cause analysis for agentic coding tasks.
AoManohDetects failure modes and escalates pressure to enforce evidence-first debugging and verification.
