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loop-library

Find, compare, adapt, and design bounded AI-agent feedback loops with explicit checks, stop rules, guardrails, and handoffs.

AI & Automationai-agentsautomationevaluationloopsworkflows

Loop Library

Help the user reuse a published Loop Library loop when one fits. Otherwise, adapt the closest loop or design a new one through a focused interview. Treat a loop as a feedback system with terminal states, not as permission for endless autonomy.

When to Use

Use when the user asks for a loop, recurring agent workflow, automation cadence, iterative improvement process, existing Loop Library recommendation, or help turning an outcome into a bounded copy-ready loop through a short question-led design session.

_Source: Forward-Future/loop-library (MIT)._

Route the request

Choose the smallest useful path:

  • Find: Recommend one to three published loops for a stated problem.
  • Adapt: Start from a published loop and replace its thresholds, tools,
  • cadence, owners, or checks without weakening its feedback cycle.

  • Design: Ask a few plain-language questions, then produce a new bounded
  • loop.

  • Find, then design: Search first. Use the nearest published loop as a
  • scaffold and ask only about the missing decisions.

Do not ask for information the user already supplied. If the request is vague, begin with: "What would you like the agent to get done?"

Find a published loop

  1. Start from [references/catalog.md](references/catalog.md), the reviewed
  2. offline catalog bundled with this skill.

  3. R

Subscribers only

The full skill, its 3 bundled files and every download is included with every paid Complete AI plan.

Details

SourceForward-Future/loop-library
LicenseMIT
Risk labelsafe ("critical" means the skill may run commands or touch files — read before use)
FilesSKILL.md, agents/openai.yaml, references/catalog.md
Added2026-06-19

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