Best use case
ralph-status is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
It is a strong fit for teams already working in Codex.
Check status of current or previous agent loop
Teams using ralph-status should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/ralph-status/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How ralph-status Compares
| Feature / Agent | ralph-status | Standard Approach |
|---|---|---|
| Platform Support | Codex | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Check status of current or previous agent loop
Which AI agents support this skill?
This skill is designed for Codex.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Al Status
Check the status of agent loops.
## Usage
```
/ralph-status # Current loop status
/ralph-status --verbose # Detailed iteration history
/ralph-status --latest # Show latest completion report
/ralph-status --all # List all completion reports
```
## Your Actions
### Default (Current Loop)
1. Read `.aiwg/ralph/current-loop.json`
2. Display status summary
**If active loop exists**:
```
Agent Loop: ACTIVE
Task: {task}
Completion: {completion}
Progress: {current}/{max} iterations
Duration: {elapsed}
Status: {running | paused}
Last iteration:
Result: {result}
Learnings: {learnings}
Use /ralph-resume to continue or /ralph-abort to stop.
```
**If no active loop**:
```
No active agent loop.
Use /ralph "task" --completion "criteria" to start one.
```
### --verbose
Include full iteration history:
```
Agent Loop: ACTIVE
Task: {task}
Completion: {completion}
Progress: {current}/{max} iterations
Iteration History:
| # | Time | Action | Result | Learnings |
|---|------|--------|--------|-----------|
| 1 | 10:30 | Initial attempt | 3 failures | Need auth mocks |
| 2 | 10:32 | Added mocks | 1 failure | Date edge case |
| 3 | 10:34 | Fixed date | In progress... | - |
```
### --latest
Read and display most recent completion report:
1. Find latest `completion-*.md` in `.aiwg/ralph/`
2. Display contents
### --all
List all completion reports:
```
Agent Loop History
| Date | Task | Status | Iterations |
|------|------|--------|------------|
| 2025-01-15 10:45 | Fix auth tests | SUCCESS | 3 |
| 2025-01-14 15:20 | Migrate to ESM | SUCCESS | 8 |
| 2025-01-13 09:00 | Add coverage | MAX_ITER | 10 |
View report: /ralph-status --report 2025-01-15
```
## State File Location
- Current loop: `.aiwg/ralph/current-loop.json`
- Iterations: `.aiwg/ralph/iterations/`
- Reports: `.aiwg/ralph/completion-*.md`
## Error Handling
**No state directory**:
```
Al has not been used in this project yet.
Get started with:
/ralph "your task" --completion "verification command"
Or:
/ralph --interactive
```
**Corrupted state**:
```
agent loop state file is corrupted.
Options:
1. Delete and start fresh: rm -rf .aiwg/ralph/
2. Check file manually: cat .aiwg/ralph/current-loop.json
```
## References
- @$AIWG_ROOT/agentic/code/addons/ralph/README.md — Ralph addon overview and loop executor documentation
- @$AIWG_ROOT/docs/cli-reference.md — CLI reference for ralph-status and related commands
- @$AIWG_ROOT/agentic/code/addons/aiwg-utils/rules/vague-discretion.md — Loop completion and iteration limit rules
- @$AIWG_ROOT/agentic/code/frameworks/sdlc-complete/README.md — SDLC framework contextRelated Skills
customize-status
Show current AIWG customization status — mode, source path, what you've customized vs upstream
soul-status
Show SOUL.md enforcement state across all installed providers with quality check
rlm-status
Show status of RLM task tree execution
research-status
Show research corpus health and statistics
ralph-resume
Resume an interrupted agent loop from last checkpoint
ralph-reflect
View and manage agent loop reflections and episodic memory
ralph-memory
Manage Al semantic memory entries — list, query, and clear lessons learned across loop iterations
ralph-external
Crash-resilient external loop with state persistence and CI/CD integration
ralph-config
View and configure agent loop settings — show, set, reset, and apply named presets
ralph-attach
Attach to a running agent loop's live output stream
ralph-analytics
Show analytics and metrics from agent loop execution history
ralph-abort
Abort a running agent loop and optionally revert changes