- 📁 agents/
- 📁 assets/
- 📁 references/
- 📄 SKILL.md
Inspect external prediction model implementations and adapt them to EasyTSF task contracts. Use when the user provides model code, class definitions, forward logic, or config fragments and wants Codex to classify the target task as `sequence_prediction`, `graph_prediction`, or `grid_prediction`, determine the current repository fit, and produce either a direct adaptation plan or a repository extension plan.
This skill should be used when the user asks to "set up OpenClaw", "get started", "onboard me", "plan my setup", or "help me choose channels". Conducts an interactive interview, then generates a tailored deployment plan.
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".
- 📁 docs/
- 📁 examples/
- 📁 references/
- 📄 .gitignore
- 📄 AGENTS.md
- 📄 LICENSE
Adversarial AI code/plan review. Codex reviews, Claude fixes, iterative loop until approved. Auto-detects plan/code/code-vs-plan mode.
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".
Use inside the plan plugin when the user wants to execute an existing implementation plan, continue from the authoritative Linear issue plan, or resume work after leaving Plan mode. Consumes the routed Linear issue identity plus the canonical linked-document `tracked-plan/1`, requires valid tracked-plan and plan-event helpers before execution, updates only tracked-plan runtime state, and appends validated progress events instead of inferring authority from chat.
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".
Converts a Lousy Agents spec or master plan into a structured Beads (bd) dependency graph of epics and tasks. Use when asked to 'convert plan to issues', 'create beads from spec', 'populate beads', 'plan to graph', or 'break down spec into tasks'.
Multi-agent development workflow using Agent Teams. Supports five modes: plan (architect teammate + PM teammate debate → plan.md), dev (developer teammate + code-tester teammate + qa-tester teammate + reviewer teammate iterate → code), full (plan → approval gate → dev), auto (plan → dev, no gate), and bugfix (tester + developer + reviewer TDD triad → fix + PR). Use when tasks benefit from collaborative agent teammates with peer messaging.
Use when you have a written plan and want it reviewed for architecture, scope, and test coverage before execution. Use when the user says "review this plan", "autoplan", "check my plan", "is this plan solid", or before running superpowers:executing-plans or superpowers:subagent-driven-development.
- 📁 agents/
- 📁 references/
- 📄 SKILL.md
Create or update a structured JSON gameplan for a codebase change, including patch sequencing, dependency graph, acceptance criteria, and formal per-patch and final-state specs. Use when the user asks for a gameplan, implementation plan, milestone plan, or structured change plan.
