claude

agent-loop

Iterative AI coding loops with automatic recovery - iteration beats perfection

229 on GitHubby AIWG Contributorsv2026.11.5MITupdated todayproductivity
/

Plugin agent-loop from marketplace aiwg in jmagly/aiwg. Commands read from the repo's manifest — today.

What it installs

Skills (18)

  • agent-loop-ext

    Crash-resilient external agent loop with state persistence and CI/CD integration

  • agent-loop

    Detect requests for iterative autonomous agent loops and route to the appropriate loop executor

  • auto-test-execution

    Automatically execute tests when code-generating agents modify source files, enforcing the execute-before-return pattern

  • cross-task-learner

    Enable agent loops to learn from similar past tasks and share patterns across loops

  • debug-memory

    Query and manage the executable feedback debug memory

  • execute-feedback

    Execute tests on generated code and iterate until passing

  • infer-completion-criteria

    Infer measurable completion criteria for an agent-loop task from project docs, code, and AIWG standards when the user has not supplied --completion explicitly

  • mission-control

    Orchestrate multi-loop background operations via the Mission Control dashboard — start sessions, dispatch missions, monitor, and stop

  • ralph-abort

    Abort a running agent loop and optionally revert changes

  • ralph-analytics

    Show analytics and metrics from agent loop execution history

  • ralph-attach

    Attach to a running agent loop's live output stream

  • ralph-config

    View and configure agent loop settings — show, set, reset, and apply named presets

  • ralph-memory

    Manage Al semantic memory entries — list, query, and clear lessons learned across loop iterations

  • ralph-reflect

    View and manage agent loop reflections and episodic memory

  • ralph-resume

    Resume an interrupted agent loop from last checkpoint

  • ralph-status

    Check status of current or previous agent loop

  • ralph

    Execute iterative task loop until completion criteria are met - iteration beats perfection

  • reflection-injection

    Inject relevant past reflections into agent context at iteration start so agents learn from prior mistakes without repeating them

Subagents (3)

  • mc-conductor

    Mission Control conductor — orchestrates parallel background missions, handles completions and failures, reports to the user

  • Agent Loop Orchestrator

    Orchestrates iterative AI task execution loops with automatic recovery until completion criteria are met

  • Al Verifier

    Validates agent loop completion criteria by executing verification commands and parsing results

View source on GitHub aiwg.io

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