status

Show DAG state, agent progress, and branch status for an AgentHub session.

25 stars

Best use case

status is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Show DAG state, agent progress, and branch status for an AgentHub session.

Teams using 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

$curl -o ~/.claude/skills/status/SKILL.md --create-dirs "https://raw.githubusercontent.com/ComeOnOliver/skillshub/main/skills/alirezarezvani/claude-skills/status/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/status/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How status Compares

Feature / AgentstatusStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Show DAG state, agent progress, and branch status for an AgentHub session.

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.

SKILL.md Source

# /hub:status — Session Status

Display the current state of an AgentHub session: agent branches, commit counts, frontier status, and board updates.

## Usage

```
/hub:status                        # Status for latest session
/hub:status 20260317-143022        # Status for specific session
```

## What It Does

1. Run session overview:
```bash
python {skill_path}/scripts/session_manager.py --status {session-id}
```

2. Run DAG analysis:
```bash
python {skill_path}/scripts/dag_analyzer.py --status --session {session-id}
```

3. Read recent board updates:
```bash
python {skill_path}/scripts/board_manager.py --read progress
```

## Output Format

```
Session: 20260317-143022 (running)
Task: Optimize API response time below 100ms
Agents: 3 | Base: dev

AGENT    BRANCH                                        COMMITS  STATUS     LAST UPDATE
agent-1  hub/20260317-143022/agent-1/attempt-1         3        frontier   2026-03-17 14:35:10
agent-2  hub/20260317-143022/agent-2/attempt-1         5        frontier   2026-03-17 14:36:45
agent-3  hub/20260317-143022/agent-3/attempt-1         2        frontier   2026-03-17 14:34:22

Recent Board Activity:
  [progress] agent-1: Implemented caching, running tests
  [progress] agent-2: Hash map approach working, benchmarking
  [results]  agent-2: Final result posted
```

Example output for a content task:

```
Session: 20260317-151200 (running)
Task: Draft 3 competing taglines for product launch
Agents: 3 | Base: dev

AGENT    BRANCH                                        COMMITS  STATUS     LAST UPDATE
agent-1  hub/20260317-151200/agent-1/attempt-1         2        frontier   2026-03-17 15:18:30
agent-2  hub/20260317-151200/agent-2/attempt-1         2        frontier   2026-03-17 15:19:12
agent-3  hub/20260317-151200/agent-3/attempt-1         1        frontier   2026-03-17 15:17:55

Recent Board Activity:
  [progress] agent-1: Storytelling angle draft complete, refining CTA
  [progress] agent-2: Benefit-led draft done, testing urgency variant
  [results]  agent-3: Final result posted
```

## After Status

If all agents have posted results:
- Suggest `/hub:eval` to rank results

If some agents are still running:
- Show which are done vs in-progress
- Suggest waiting or checking again later

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