# Full Cycle > Use when this capability is needed. - Skill: `tomevault-io/full-cycle` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/full-cycle` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/full-cycle/raw - Safety review: pending (external: skill-scanner PASS, skillspector WARNING) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/full-cycle --- --- name: full-cycle description: This skill should be used when the user asks for a "full review and fix", "find and fix issues", "review and implement", "end-to-end review", "audit and fix", "comprehensive review", "full-cycle review", or wants experts to find issues AND have them automatically implemented (not just reviewed). Use /mira:experts instead if the user only wants opinions or analysis without code changes. argument-hint: "[focus area or --discovery-only]" --- # Full-Cycle Review > **Requires:** Claude Code Agent Teams feature. End-to-end expert review with automatic implementation and QA verification. **Arguments:** $ARGUMENTS ## Instructions 1. **Parse arguments** (optional): - `--discovery-only` -> Only run Phase 1 (same as `/mira:experts`) - `--skip-qa` -> Skip Phase 3 QA verification - `--members nadia,sable` -> Only spawn these specific discovery experts (by first name) - Any other text -> use as the context/focus for the review 2. **Determine context**: The user's question, the area to review, or the scope of analysis. If no context is obvious, ask the user what they'd like reviewed. --- ### Phase 1: Discovery 3. **Launch discovery team**: Call the Mira `launch` MCP tool to get agent specs: ``` launch(team="expert-review-team", scope=user_context, members="nadia,sable" or omit for all) ``` The `members` parameter is only needed if the user passed `--members`. 4. **Create the team**: ``` TeamCreate(team_name=result.data.suggested_team_id) ``` 5. **Create and assign discovery tasks**: For each agent in `result.data.agents`: ``` TaskCreate(subject=agent.task_subject, description=agent.task_description) TaskUpdate(taskId=id, owner=agent.name, status="in_progress") ``` 6. **Spawn discovery experts**: For each agent in `result.data.agents`, use the `Task` tool: ``` Task( subagent_type="general-purpose", name=agent.name, model=agent.model, team_name=result.data.suggested_team_id, prompt=agent.prompt + "\n\n## Context\n\n" + user_context, run_in_background=true ) ``` Spawn all discovery experts in parallel (multiple Task calls in one message). IMPORTANT: Do NOT use `mode="bypassPermissions"` for discovery agents -- they are read-only explorers. IMPORTANT: Always pass model="sonnet" to the Task tool. This ensures read-only agents use a cost-efficient model. 7. **Wait for findings**: All discovery experts will send findings via SendMessage. Wait for all to finish, then shut them down. --- ### Phase 2: Synthesis + Implementation 8. **Synthesize findings** into a unified report: - **Consensus**: Points multiple experts agree on - **Key findings per expert**: Top findings from each specialist - **Tensions**: Where experts disagree -- present both sides with evidence - **Prioritized action items**: Concrete fixes grouped by file ownership IMPORTANT: Preserve genuine disagreements. Do NOT force consensus. 9. **Present synthesis to user** and WAIT for their approval before proceeding to implementation. Do not auto-proceed. 10. **Launch implementation team**: Call `launch` to get implementation agent specs: ``` launch(team="implement-team", scope=approved_items) ``` 11. **Spawn Kai (implementation planner)** from the launch results: ``` Task( subagent_type="general-purpose", name="kai", model=kai_agent.model, team_name=implement_result.data.suggested_team_id, prompt=kai_agent.prompt + "\n\n## Approved Findings\n\n" + approved_items, run_in_background=true ) ``` Kai groups fixes by file ownership, identifies dependencies, and sets max 3-5 fixes per agent. 12. **Spawn implementation agents** based on Kai's work breakdown: ``` Task( subagent_type="general-purpose", name="fixer-{group-name}", team_name=implement_result.data.suggested_team_id, # result from step 10's launch call prompt=implementation_prompt + task_descriptions, run_in_background=true, mode="bypassPermissions" ) ``` Follow the implement-team coordination rules: strict file ownership, max 3-5 fixes per agent, schema changes first, verify with `cargo test --no-run` (NEVER --release). Spawn all implementation agents in parallel. Monitor build diagnostics and send hints if needed. 13. **Spawn Rio (integration verifier)** from the launch results after implementation agents complete: ``` Task( subagent_type="general-purpose", name="rio", model=rio_agent.model, team_name=implement_result.data.suggested_team_id, prompt=rio_agent.prompt + "\n\n## Changes Made\n\n" + summary_of_changes, run_in_background=true, mode="bypassPermissions" ) ``` Rio runs compilation checks, linters, tests, and fixes cross-agent issues. 14. **Wait for implementation**: All agents report completion via SendMessage. Shut them down. --- ### Phase 3: QA Verification 15. **Launch QA team**: Call `launch` to get QA agent specs: ``` launch(team="qa-hardening-team", scope=summary_of_changes) ``` 16. **Spawn QA agents**: For each agent in the QA launch results: ``` Task( subagent_type="general-purpose", name=agent.name, model=agent.model, team_name=qa_result.data.suggested_team_id, # result from step 15's launch call prompt=agent.prompt + "\n\n## Changes Made\n\n" + summary_of_changes, run_in_background=true ) ``` IMPORTANT: Do NOT use `mode="bypassPermissions"` for QA agents -- they are read-only. IMPORTANT: Always pass model="sonnet" to the Task tool. This ensures read-only agents use a cost-efficient model. 17. **Create and assign QA tasks** for each auditor. 18. **Wait for QA results**: If issues found, either fix directly or spawn additional fixers. --- ### Phase 4: Finalize 19. **Verify** final build: `cargo clippy --all-targets --all-features -- -D warnings` + `cargo fmt --all -- --check` + `cargo test` (NEVER --release). 20. **Shut down** all remaining agents. 21. **Report** final summary to user with all changes made. 22. **Cleanup**: `TeamDelete` ### Handling Stalled Agents If an agent has not responded after an unusually long time, send it a direct message via SendMessage to check status. For discovery agents, shut down if unresponsive and note the gap. For implementation agents, fix directly or reassign. Do not wait indefinitely. ## Examples ``` /mira:full-cycle -> Prompts for what to review, then runs full discovery -> implementation -> QA cycle /mira:full-cycle Review the database layer for issues -> 4 experts review the DB layer, findings are implemented, QA verifies /mira:full-cycle --discovery-only -> Only runs Phase 1 (equivalent to /mira:experts) /mira:full-cycle --skip-qa -> Runs discovery + implementation but skips QA phase /mira:full-cycle --members nadia,jiro -> Only Nadia and Jiro run discovery, then full implementation + QA cycle ``` ## Phases and Agents | Phase | Agents | Purpose | |-------|--------|---------| | Discovery | Nadia, Jiro, Sable, Lena (expert-review-team) | Find issues, propose improvements | | Implementation | Kai plans, dynamic agents execute, Rio verifies (implement-team) | Implement fixes in parallel | | QA | Hana, Orin, Kali, Zara (qa-hardening-team) | Verify changes, catch regressions | --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/conarylabs) — claim your Tome and manage your conversions.