LoopOps Guide
June 14, 2026 ยท View on GitHub
LoopOps is the ABVX discipline for deciding when agent behavior should remain a prompt and when it should be promoted into a more durable artifact.
The core rule is simple: do not turn every repeated task into a skill. Promote only when reuse, reliability, or cost control justifies the overhead.
Promotion Ladder
- Prompt
- one-off task
- low cost of repetition
- no recurring failure mode
- Checklist
- same task repeats
- sequence matters
- human or agent keeps forgetting a step
- Skill
- workflow is reusable and procedural
- trigger language is stable
- the instructions improve outcomes across tasks
- Script
- a deterministic step keeps getting rewritten
- reliability matters more than prose flexibility
- Loop / workflow
- the task spans multiple cycles
- a bounded evaluator, memory policy, and stop rule are needed
Decision Heuristics
- Stay at the lowest artifact that reliably solves the problem.
- Prefer a prompt when the variation surface is high and the task is still cheap.
- Prefer a skill when the reusable value is procedural rather than code-level deterministic.
- Prefer a script when the same code keeps being generated.
- Prefer a loop only when bounded repetition beats manual supervision.
Anti-Patterns
- turning one successful prompt into a published skill immediately;
- using a skill to hide the absence of verification;
- adding a loop without budget, stop rules, or escalation;
- building a script when a two-line shell command already works;
- turning local repo context into a "universal" skill without proving portability.
Example: Prompt -> Skill
Situation:
- repeated repo tasks require the same "read narrowly, patch small, verify honestly" execution style
- the advice is procedural, not deterministic code
Promotion:
- prompt guidance becomes
token-efficient-execution
Why not script:
- the value is in agent behavior shaping, not a deterministic transformation
Example: Skill -> Script
Situation:
- a skill keeps re-explaining the same JSON export, data extraction, or harness bootstrap code
Promotion:
- keep the workflow in
SKILL.md - move the deterministic step into
scripts/
Why:
- lower token cost
- fewer implementation drifts
Example: Skill -> Loop
Situation:
- repeated task flow now needs:
- a fixed budget,
- memory policy,
- evaluator,
- escalation rule,
- bounded retries
Promotion:
- use
loopops-protocolanddynamic-workflow-packetsto decide whether the work should become a supervised loop or packetized workflow
Recommended Pairings
loopops-protocol+skillopt-evolve-skillsloopops-protocol+dynamic-workflow-packetstoken-efficient-executionbefore promoting a workflow that may only be noisy rather than truly reusabledelivery-preflight-gatebefore longer autonomous loops
Practical Rule
If you cannot explain:
- what recurring failure or cost this promotion fixes,
- why the lower artifact is insufficient,
- how the promoted artifact will be validated,
then do not promote it yet.