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Overview
Provides async human-in-the-loop decision review by pushing structured decision plans to Arbiter Zebu and retrieving finalized answers for agents to act on.
Key Advantages
1.Enables explicit human oversight on critical plans, architecture choices, and blocking decisions.
2.Structured JSON schema for decisions ensures clarity and consistency for reviewers.
3.Tight integration with agent context via CLAWDBOT_AGENT and CLAWDBOT_SESSION environment variables.
4.Supports both polling and blocking wait patterns (status, get, await) for flexible orchestration.
5.Tagging, priority, and notification mechanisms make it suitable for multi-agent, multi-project environments.
Use Cases
- Getting human approval on high-impact architectural decisions before implementation.
- Reviewing complex project plans or rollout strategies that involve tradeoffs and risk.
- Coordinating multiple related decisions (e.g., auth strategy, database, caching) as a single reviewable batch.
- Unblocking agents that must not proceed without explicit human sign-off on key choices.
- Establishing governance or compliance checkpoints in automated development or operations workflows.
Evaluation Scores
8.1
/ 10
Reliability
7.5
Functionality
8.0
Usability
8.5
Safety
9.0
Performance
7.0
Compatibility
7.5
Based on 1 evaluation · Latest: 3/20/2026
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Evaluation History (1)
8.1/103/20/2026▼
OS: linux-arm64LLM: minimax/minimax-m2.5
**Judgement:** A well-designed, specialized skill for adding structured human-in-the-loop decision review into agent workflows. Very suitable where human approval or oversight is mandatory; unnecessary overhead for routine tasks.
**Key strengths:**
- Strong fit for governance, compliance, or high-risk technical decisions that should not be fully automated.
- Clear JSON schema for decisions and options, with solid examples and CLI parity.
- Good support for async patterns: push, status, get, and await, plus tagging and notifications for agents.
**Main risks / limitations:**
- Requires an external Arbiter Zebu bot and filesystem-based queue; if that infrastructure isn’t running or is misconfigured, the skill becomes non-functional.
- Not appropriate for urgent real-time decisions; latency depends on human reviewers.
- Potential data-exposure risk if sensitive context is pushed to Arbiter without proper access controls.
**Recommended scenarios:**
- Use for architectural decisions, plan reviews, and any blocking choices where you explicitly want human judgment before proceeding.
- Use tags and notify fields to integrate into multi-agent or multi-project environments that have a regular “arbiter review” process.
- Avoid using it for simple, low-impact questions or anything requiring immediate answers; in those cases, either decide autonomously or route via a direct human message instead.
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