Agent skill
plan
Research the codebase and create an implementation plan following Propose/Justify/Recommend. Use this before any feature, fix, or refactor.
Install this agent skill to your Project
npx add-skill https://github.com/cortex-tms/cortex-tms/tree/main/.claude/skills/plan
SKILL.md
Plan
You are planning a feature for Cortex TMS. Enter plan mode immediately.
Rules
- Enter plan mode — use EnterPlanMode before doing anything else
- Research first — read relevant source files, tests, docs, and patterns before proposing anything
- Follow Propose/Justify/Recommend:
- Propose: What you will build and how
- Justify: Why this approach, with evidence from the codebase
- Recommend: One clear recommendation — then stop and wait
- Write the plan — update NEXT-TASKS.md with a sprint checklist (- [ ] items) and acceptance criteria
- Update task files if needed:
- Move tasks between NEXT-TASKS.md and FUTURE-ENHANCEMENTS.md
- Update status markers in FUTURE-ENHANCEMENTS.md
- Archive completed sprints to docs/archive/
- Exit plan mode — present the plan for user approval via ExitPlanMode
- STOP — do not write any code. Wait for the user to approve or give feedback.
You CANNOT
- Touch any file in src/, bin/, templates/
- Edit README.md, package.json, or any config file
- Write code, tests, or build artifacts
- Run build, test, or lint commands
- Proceed to implementation without explicit user approval
Arguments
$ARGUMENTS
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
new-command
Scaffold a new CLI command for Cortex TMS following the existing codebase patterns.
release
Guide through the Cortex TMS release process — version bump, changelog, sync, tag, publish. Every step requires user approval.
sync
Synchronize task files and source-of-truth documents. Update NEXT-TASKS.md, FUTURE-ENHANCEMENTS.md, README, and CHANGELOG to reflect current project state.
implement
Implement an approved plan. Write code, tests, and docs following the sprint checklist in NEXT-TASKS.md.
validate
Run the full quality gate — tests, lint, build, and cortex-tms validate --strict.
verl-rl-training
Provides guidance for training LLMs with reinforcement learning using verl (Volcano Engine RL). Use when implementing RLHF, GRPO, PPO, or other RL algorithms for LLM post-training at scale with flexible infrastructure backends.
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