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clarkchenkai

Feedback Controller

by Cubic AI · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install feedback-controller-clarkchenkai
Description
Feedback Controller — Closed-Loop Agent Skill for Correcting Execution Drift. Use it when the user needs a disciplined protocol and fixed output contract for...
README (SKILL.md)

Feedback Controller — Closed-Loop Agent Skill for Correcting Execution Drift

Use this skill when the task matches the protocol below.

Activation Triggers

  • multi-step execution drift
  • an output exists but does not meet the brief
  • tool failures, stale context, or partial retries
  • quality checks after writing, analysis, or workflow automation
  • cases where the real question is not 'did it run?' but 'did it converge?'

Core Protocol

Step 1: Define the target state

Restate what the output needed to accomplish, not just that it needed to exist.

Step 2: Compare current state against target

Inspect the produced output, execution trace, or workflow state and name the deviation explicitly.

Step 3: Localize the error source

Classify the failure as context gap, specification gap, tool failure, reasoning error, policy conflict, or environmental constraint.

Step 4: Choose the smallest effective control action

Prefer local correction over full rewrite when possible. Decide whether to retry, switch tools, narrow scope, rewrite, or escalate.

Step 5: Set a stop condition

Do not permit endless correction loops. State what would count as success, and what triggers human escalation.

Output Contract

Always end with this six-part structure:

## Target State
[...]

## Current State
[...]

## Observed Deviation
[...]

## Error Source
[...]

## Correction Strategy
[...]

## Escalation Decision
[...]

Response Style

  • Be specific about the deviation, not vague about quality.
  • Prefer typed error diagnoses over generic 'try again' advice.
  • Use partial correction when the problem is local.
  • Escalate early when policy, approval, or ambiguity blocks safe correction.

Boundaries

  • It does not replace the original goal definition. It assumes a target already exists.
  • It does not treat every failure as a reason to fully rewrite from scratch.
  • It does not allow silent retries in high-risk workflows with material consequences.
Usage Guidance
This skill is internally consistent and does what it says: a disciplined protocol for diagnosing and correcting drift. It does not ask for credentials or install code. The main operational concern is scope: the protocol explicitly allows retries and tool switching, so review and constrain the agent's tool permissions and implicit-invocation settings if you want to prevent automated corrective actions in high‑risk workflows. If you require human approval for escalations or changes with material consequences, enforce that in the agent policy or by disabling implicit invocation for this skill.
Capability Analysis
Type: OpenClaw Skill Name: feedback-controller-clarkchenkai Version: 1.0.0 The feedback-controller skill is a meta-utility designed to help an AI agent self-correct and diagnose execution drift through a structured feedback loop. It provides a disciplined protocol for error classification and correction strategies, with explicit instructions in SKILL.md and references/escalation.md to escalate to a human in high-risk or ambiguous scenarios. No malicious code, data exfiltration, or unauthorized execution capabilities were found.
Capability Assessment
Purpose & Capability
Name, description, and provided materials (protocol, patterns, escalation rules) match the stated purpose. No unrelated env vars, binaries, or install steps are requested.
Instruction Scope
SKILL.md confines the agent to a five‑step correction protocol and a fixed six‑part output contract. It does grant the agent discretion to 'retry, switch tools, narrow scope, rewrite, or escalate' and to inspect produced outputs and execution traces — reasonable for a correction controller but broad in practice. If you need to limit automatic tool switching or retries, enforce those constraints at the agent/tool-permission level.
Install Mechanism
Instruction-only skill with no install spec and no code to write to disk; lowest-risk install footprint.
Credentials
No environment variables, credentials, or config paths are required or referenced. The skill does not request secrets or external service tokens.
Persistence & Privilege
Registry flags show normal autonomous invocation allowed (disable-model-invocation: false). agents/openai.yaml sets allow_implicit_invocation: true, which may let the platform call this skill automatically in some contexts — not inherently dangerous, but if you want tighter control, consider disabling implicit invocation or restricting when the agent can apply correction actions.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install feedback-controller-clarkchenkai
  3. After installation, invoke the skill by name or use /feedback-controller-clarkchenkai
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of the feedback-controller skill: - Introduces a closed-loop protocol for correcting execution drift in multi-step tasks. - Defines a clear, six-part output contract for structured feedback. - Specifies step-by-step diagnostic and corrective procedures, including triggers and boundaries. - Emphasizes specific error localization and partial correction over generic or total rework. - Details escalation rules to prevent endless correction loops in automated workflows.
Metadata
Slug feedback-controller-clarkchenkai
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Feedback Controller?

Feedback Controller — Closed-Loop Agent Skill for Correcting Execution Drift. Use it when the user needs a disciplined protocol and fixed output contract for... It is an AI Agent Skill for Claude Code / OpenClaw, with 91 downloads so far.

How do I install Feedback Controller?

Run "/install feedback-controller-clarkchenkai" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Feedback Controller free?

Yes, Feedback Controller is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Feedback Controller support?

Feedback Controller is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Feedback Controller?

It is built and maintained by Cubic AI (@clarkchenkai); the current version is v1.0.0.

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