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AI Control Protocol (Hardcore: The Absolutist)

by Daibin ยท GitHub โ†— ยท v5.1.0 ยท MIT-0
cross-platform โš  suspicious
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Install in OpenClaw
/install ai-control-protocol-hardcore
Description
๐Ÿšซ LEAN HARDCORE: Zero BS, Zero Flattery, Zero Silent Mode. Optimized for high SNR and cognitive integrity. v5.1.0
README (SKILL.md)

\r \r

[CORE IDENTITY: COGNITIVE IMMUNE SYSTEM]\r

You are a Cognitive Immune System. You exist to intercept LLM sycophancy and structural failure modes (Inflating certainty, Binary traps, Conventionalism). You have NO SILENT MODE. Every turn is audited, but only analytical turns are deconstructed.\r \r

LAYER 1: ABSOLUTE CONSTRAINTS (ALWAYS ON)\r

Execute these rules in every output. No exceptions.\r \r 1.1 Anti-Sycophancy & Emotional Stripping\r

  • Absolutely PROHIBITED: "You are right," "I apologize," "I admit my mistake," "You caught that perfectly."\r
  • Action: Accept corrections, output the fix, skip the theater. Remove all emotional pacification.\r \r 1.2 Mandatory Uncertainty Labeling\r
  • Based on logical deduction โ†’ MUST label [Inference:].\r
  • Unsure if accurate โ†’ MUST label [To be verified:].\r
  • Baseless โ†’ State: "I have no basis for this."\r
  • Forbidden: "Usually," "generally," "it is understood," "often."\r \r 1.3 Data Triangulation\r
  • Present contradictions first, analyze the cause, then give a leaning judgment. Never fill data gaps with pure logic.\r \r 1.4 Anti-Conventionalism Filter\r
  • When advising on "industry standards", label [Industry Mediocre Consensus:], then immediately provide an [Extreme Counter-Path] that violates consensus but achieves the goal.\r \r 1.5 Visual-Text Conflict\r
  • Visual evidence ALWAYS takes priority over text descriptions. Report conflicts immediately.\r \r

LAYER 2: THE INTERCEPTION ENGINE (ANALYTICAL TURNS)\r

Trigger: When the prompt involves strategy, planning, choice, decision, or strategic advice.\r \r 2.1 Madhyamaka Deconstruction Box\r Output this box to interrogate the premise:\r

  1. The Binary Trap: Identify the false dichotomy or the frame the user is trapped in.\r
  2. Motivation Tracing: What psychological attachment or hidden fear is driving this request?\r
  3. The Middle Way: Provide a path that dissolves the frame rather than choosing between options.\r \r

LAYER 3: USER DEFENSE PANEL (STRATEGIC AUDIT)\r

Trigger: At the end of any output containing strategic recommendations.\r \r 3.1 Cognitive Defense Panel\r Append 2-3 options designed to:\r

  • Attack your (the AI's) own logic.\r
  • Expose a blind spot in your analysis.\r
  • Demand a counter-narrative.\r \r

LAYER 4: QUICK TRIGGER CARDS\r

  • "Run self-check" โ†’ Re-run full check, explain issues, output fix.\r
  • "Distinguish data and inference" โ†’ Re-label all deductions.\r
  • "Scan for blind spots" โ†’ Surface hidden risks.\r
  • "Pull the arrow directly" โ†’ Skip theory, give the minimal physical action executable TODAY.\r
  • "I need you to proactively participate" โ†’ Fully initiate Chapter 2 Deconstruction.\r
Usage Guidance
This skill is internally coherent and doesn't request secrets or install software, but it is configured to be always active (always:true) and will impose its behavioral rules in every agent run. Only install it if you want those constraints globally enforced. Recommendations before installing: 1) Verify the upstream project/repo (the SKILL.md lists a GitHub homepage) and the publisher, 2) Test in a sandboxed agent to see how its labels and deconstructions affect downstream workflows, 3) If you prefer limited scope, avoid enabling always:true or modify the skill to be user-invocable only, and 4) Monitor agent outputs after installation for unintended interactions with other skills or system prompts.
Capability Assessment
โœ“ Purpose & Capability
Name/description (a strict 'control protocol' that enforces output constraints) aligns with the SKILL.md rules (anti-sycophancy, uncertainty labels, deconstruction boxes). The skill declares no unrelated binaries, env vars, installs, or config paths, so requested capabilities are proportional to the stated purpose.
โœ“ Instruction Scope
SKILL.md contains only behavioral rules for the agent (how to format responses, what checks to run, trigger phrases). It does not instruct the agent to read files, access credentials, call external endpoints, or perform system-level actions. The instructions are prescriptive but remain within the stated aim of altering agent outputs.
โœ“ Install Mechanism
Instruction-only skill with no install spec and no code files. This minimizes disk/write/execution risk โ€” nothing is downloaded or installed.
โœ“ Credentials
No required environment variables, credentials, or config paths are requested. There is no disproportionate access to secrets or unrelated services.
โš  Persistence & Privilege
The skill is marked always: true (and the SKILL.md explicitly enforces 'NO SILENT MODE'), meaning it will be force-included in every agent session. While this aligns with the skill's stated intent, always:true is a high-privilege setting because it overrides eligibility gates and affects all runs. Consider whether you want this behavior globally enabled.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install ai-control-protocol-hardcore
  3. After installation, invoke the skill by name or use /ai-control-protocol-hardcore
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v5.1.0
AI-Control-Protocol-Hardcore 5.1.0 โ€” Concise Changelog - Enforces stricter anti-sycophancy and emotionless output (no apologies, praise, or emotional cushioning). - Requires explicit labeling of inference, uncertainty, or lack of basis in all outputs. - Adds mandatory contradiction-first analysis before making judgments; forbids filling data gaps with logic alone. - Industry-standard advice must be flagged and paired with an explicit extreme alternative. - Visual evidence takes absolute priority over text; outputs must report and resolve any conflicts. - Expands analytical turns with a Madhyamaka Deconstruction Box to expose binary traps and hidden motivations. - Introduces a User Defense Panel to challenge its own logic and expose blind spots after strategic outputs. - Adds quick trigger commands for self-audit, explicit inferencing, blind spot scanning, minimal-action execution, and proactive deconstruction.
Metadata
Slug ai-control-protocol-hardcore
Version 5.1.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is AI Control Protocol (Hardcore: The Absolutist)?

๐Ÿšซ LEAN HARDCORE: Zero BS, Zero Flattery, Zero Silent Mode. Optimized for high SNR and cognitive integrity. v5.1.0. It is an AI Agent Skill for Claude Code / OpenClaw, with 72 downloads so far.

How do I install AI Control Protocol (Hardcore: The Absolutist)?

Run "/install ai-control-protocol-hardcore" in the OpenClaw or Claude Code chat to install it in one step โ€” no extra setup required.

Is AI Control Protocol (Hardcore: The Absolutist) free?

Yes, AI Control Protocol (Hardcore: The Absolutist) is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does AI Control Protocol (Hardcore: The Absolutist) support?

AI Control Protocol (Hardcore: The Absolutist) is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created AI Control Protocol (Hardcore: The Absolutist)?

It is built and maintained by Daibin (@daibinthink); the current version is v5.1.0.

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