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loop-runner

Skill19 starsChanged 2 months agoMITView on GitHub

Execute and manage loop engineering primitives (init, run, status, audit) from an AI coding

1 other project uses a version of this.

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The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 0 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈0

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Prefer agent-toolkit loop … on PATH (V binary or PyPI launcher)

    line 54
  2. Very specific:

    When agent-toolkit loop run dispatches a loop, it tries runners in this order:

    line 59

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

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Files
SKILL.md

loop-runner

Execute and manage loop engineering primitives from an AI coding session.

What this skill does

This skill wraps the agent-toolkit loop CLI (V product command), exposing loop operations to AI coding agents without requiring the user to remember CLI flags.

Loop engineering is the practice of designing recursive, autonomous processes that prompt AI agents — as opposed to prompting agents directly. Loops have durable state (STATE.md), safety gates (allowlist/deny), cost budgets, and rollout tiers (L1 report-only → L2 PR-gated → L3 unattended).

Capabilities

SubcommandWhen to use
loop init <pattern>Scaffold a new loop from a starter
loop run <loop>Execute one loop iteration
loop statusShow all loops: tier, cadence, last run
loop audit [loop]Summarize past run success/cost
loop cost <loop>Estimate per-run token cost
loop schedule <loop>Install systemd/launchd timer
loop syncPush escalations to knowledge/todos

How to invoke

# Preferred — agent-toolkit V CLI
agent-toolkit loop status
agent-toolkit loop run daily-triage
agent-toolkit loop init oss-pr-monitor

Historical note: older docs referred to ./bin/loop or ~/.ai-workspace/bin/loop. Those entrypoints are obsolete; use agent-toolkit loop after installing via brew / AUR agent-toolkit-bin / GitHub Release / uv tool install agent-toolkit-cli.

Routing

  1. Prefer agent-toolkit loop … on PATH (V binary or PyPI launcher)
  2. Otherwise guide the user to install per docs/INSTALLATION.md

Runner hierarchy

When agent-toolkit loop run dispatches a loop, it tries runners in this order:

PriorityRunnerHow to enable
1runnerexport HARNESS_RUNNER_DIR="$HOME/.local/share/agentic-workstation/dev-companion/runner"
2claude --print (Claude Code CLI)claude in PATH — zero setup for Claude Code users
3Skeleton planAlways available

For full multi-provider support (Anthropic, OpenAI, Ollama, OpenCode), set HARNESS_RUNNER_DIR to point at the runner. Claude Code users can skip this — claude --print is used automatically.

References

Rules

  1. Always start at L1 for new loops. Only graduate to L2/L3 after reviewing at least 3 consecutive clean L1 runs.
  2. Budget awareness — report the estimated cost before running an expensive loop (pr-babysitter, ci-sweeper). Confirm with the user.
  3. Allowlist enforcement — never take an action not in the loop's allowlist. If uncertain: escalate (human_escalation exit condition).
  4. Worktree hygiene — loops create isolated git worktrees. Clean them up on success; preserve on failure for postmortem.
  5. Escalation first — when in doubt, choose human_escalation over guessing. The user can always re-run.

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