agent-loop
SolidDetect requests for iterative autonomous agent loops and route to the appropriate loop executor
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Quality Score: 93/100
Skill Content
Details
- Author
- jmagly
- Repository
- jmagly/aiwg
- Created
- 9 months ago
- Last Updated
- yesterday
- Language
- TypeScript
- License
- MIT
Integrates with
Similar Skills
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agent-loop-ext
Crash-resilient external agent loop with state persistence and CI/CD integration
autonomous-loop-patterns
This skill consolidates autonomous AI agent loop patterns: the Ralph Wiggum exit-code-2 pattern, our manage-loop (manage-continuation.json + manage-loop-hook.py), grind-loop.sh supervisor, completion detection strategies, safety caps, stall detection, and the tradeoffs between simple loops and sophisticated orchestration. Use when designing or debugging autonomous agent loops, choosing between loop approaches, or implementing safety limits. Do NOT use for choosing which command to run (use ai-coding-agents) or for task management (use linear).
learning-loop
(Industry standard: Loop Agent / Single Agent) Primary Use Case: Self-contained research, content generation, and exploration where no inner delegation is required. Self-directed research and knowledge capture loop. Use when: starting a session (Orientation), performing research (Synthesis), or closing a session (Seal, Persist, Retrospective). Ensures knowledge survives across isolated agent sessions.
dual-loop
(Industry standard: Sequential Agent / Agent as a Tool) Primary Use Case: Delegating a well-defined task to a worker agent, verifying its execution, and repeating if necessary. Inner/outer agent delegation pattern. Use when: work needs to be delegated from a strategic controller (Outer Loop) to a tactical executor (Inner Loop) via strategy packets, with verification and correction loops.
autonomous-loop-patterns
Use when designing, reviewing, or debugging an autonomous AI agent loop: repeated agent execution, completion signals, checkpoints, supervisor respawn, stall detection, safety caps, and human handoff rules. Covers the core loop patterns from simple bounded runs through sentinel-based continuation, checkpoint-resume, and external supervisor loops. Do NOT use for choosing a specific agent product command (use agent-engineering or the product's docs), writing ordinary task instructions (use prompt-craft), or optimizing individual tool calls (use tool-call-strategy).