majiayu000 Final Approach
The landing sequence for completing a mission. Runs the Go Poll to get status from all stations.
Usage
/final-approach [issue-number]
What This Does
Final Approach is the end-of-mission workflow:
- Sync - Fetch and rebase with upstream
- Check - Run
./scripts/check.sh - Go Poll - Review agents report status in
reentrymode - Landing Doc - Create summary document
- Commit - Ready for merge
Go Poll
The Go Poll launches review agents (all use Haiku model for speed):
| Agent | Model | Focus | Call |
|---|---|---|---|
| mission-control | Haiku | Plan compliance, docs | "Mission Control, go." |
| telemetry | Haiku | Test coverage, quality | "Telemetry, go." |
| flight-director | Haiku | Code quality, Unix philosophy | "Flight Director, go." |
A+ Skip Rule
If an agent gives ALL A+ in round N, skip that agent in round N+1.
Example:
Round 1: Run all 3 agents
- mission-control: A+ ← Will be skipped
- telemetry: B
- flight-director: A
Round 2: Skip mission-control, run telemetry + flight-director
- telemetry: A
- flight-director: A+ ← Will be skipped
Round 3: Skip mission-control + flight-director, run only telemetry
- telemetry: A+
Done: All agents at A or A+
Output Structure
tmp/{ISSUE}/
└── landing/
└── round-{N}/
├── mission-control.md
├── telemetry.md
└── flight-director.md
Grading Scale
| Grade | Meaning |
|---|---|
| A+ | Exceeds all standards - exemplary (skip next round) |
| A | Perfect compliance - go for landing |
| B | Minor issues - quick fixes needed |
| C | Significant gaps - more work required |
| F | Major problems - no-go |
Success Criteria
Must achieve A+ from ALL THREE agents before landing.
If any agent gives below A:
- Fix all identified issues
- Run
./scripts/check.sh - Re-run
/final-approach - Repeat until all agents report "go"
Instructions
When invoked, you MUST:
- Determine the issue number from context (git branch, plan file, or ask user)
- Determine the round number (start at 1, increment for re-reviews)
- Check previous round grades - skip agents with A+ from prior rounds
- Create the output directory:
tmp/{ISSUE}/landing/round-{N}/ - Launch agents IN PARALLEL using Task tool with
model: "haiku/sonnet" - After all agents complete, summarize the grades in a table
- If any grade is below A +, list the blocking issues that must be fixed
Example agent prompts:
Agent 1 (mission-control):
Go Poll for issue #{ISSUE} - Final Approach (Round {N}).
You are Mission Control reporting status for landing.
Focus: Plan compliance and documentation quality.
1. Find the plan file (check ~/.claude/plans/reovim/ or tmp/)
2. Verify all planned phases are implemented
3. Audit documentation quality (module docs, API docs, guides)
4. Check CHANGELOG.md for completeness
Write your report to: tmp/{ISSUE}/landing/round-{N}/mission-control.md
End with: "Mission Control: GO / NO-GO" and grade (A+/A/B/C/F).
Agent 2 (telemetry):
Go Poll for issue #{ISSUE} - Final Approach (Round {N}).
You are Telemetry reporting status for landing.
Focus: Test coverage and test quality.
1. Inventory all tests (unit and integration)
2. Analyze coverage of happy paths, error paths, edge cases
3. Detect test anti-patterns (flaky, slow, giant tests)
4. Identify missing critical test cases
Write your report to: tmp/{ISSUE}/landing/round-{N}/telemetry.md
End with: "Telemetry: GO / NO-GO" and grade (A+/A/B/C/F).
Agent 3 (flight-director):
Go Poll for issue #{ISSUE} - Final Approach (Round {N}).
You are Flight Director reporting status for landing.
Focus: Code quality and Unix philosophy compliance.
1. Verify Unix philosophy: mechanism vs policy, single responsibility, composability
2. Check layer boundaries (kernel → drivers → modules)
3. Audit unsafe code for SAFETY documentation
4. Run cargo clippy and cargo doc to verify zero warnings
5. Assess complexity and anti-patterns
Write your report to: tmp/{ISSUE}/landing/round-{N}/flight-director.md
End with: "Flight Director: GO / NO-GO" and grade (A+/A/B/C/F).
CRITICAL: Launch agents using the Task tool with:
subagent_typeset to the agent name (mission-control, telemetry, flight-director)model: "haiku"for fast, efficient reviewsmodel: "sonnet"for comprehensive, precise reviews- Skip agents that received A+ in previous rounds