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Loop Stability Check

by @clarkchenkai

Loop Stability Check — Workflow Stability Skill for Detecting Loops, Drift, and Retry Waste. Use it when the user needs a disciplined protocol and fixed outp...

Versionv1.0.0
Downloads519
TERMINAL
clawhub install loop-stability-check-clarkchenkai

📖 About This Skill


name: loop-stability-check description: | Loop Stability Check — Workflow Stability Skill for Detecting Loops, Drift, and Retry Waste. Use it when the user needs a disciplined protocol and fixed output contract for this kind of task rather than a generic answer. license: MIT metadata: author: clarkchenkai version: "1.0.0" language: en

Loop Stability Check — Workflow Stability Skill for Detecting Loops, Drift, and Retry Waste

Use this skill when the task matches the protocol below.

Activation Triggers

  • repeated retries with no improvement
  • oscillation between multiple outputs or states
  • planning loops that never cash out into execution
  • human-bot ping-pong with no stable owner
  • cases where repetition is happening but convergence is not
  • Core Protocol

    Step 1: Define the intended loop objective

    A loop cannot be judged as stable if nobody states what it is supposed to converge toward.

    Step 2: Observe the repeated behavior

    Look at retries, state changes, tool calls, or handoff cycles instead of reasoning from theory alone.

    Step 3: Classify the instability

    Name the pattern: dead retry, oscillation, drift, amplification, or feedback starvation.

    Step 4: Locate the feedback failure

    Ask which signal is missing, delayed, noisy, or being ignored.

    Step 5: Add guardrails and intervention

    Recommend retry caps, state locks, escalation triggers, ownership boundaries, or full halts where needed.

    Output Contract

    Always end with this six-part structure:

    ## Loop Objective
    [...]

    Observed Behavior

    [...]

    Stability Risks

    [...]

    Likely Failure Mode

    [...]

    Guardrails

    [...]

    Recommended Intervention

    [...]

    Response Style

  • Describe the loop behavior concretely.
  • Prefer named failure modes over generic ‘this seems buggy.’
  • Recommend the smallest guardrail that restores convergence.
  • Stop the loop when the right action is halt, not another cycle.
  • Boundaries

  • It does not optimize creativity by forcing every open-ended workflow into rigid convergence.
  • It does not confuse ‘more steps’ with ‘more learning.’
  • It does not permit repeated motion to substitute for explicit ownership and escalation.