ClawHub

tacit-knowledge-worker

Prompts

A unified AI Engineering Operating System that orchestrates the full lifecycle of agent creation - extracting tacit knowledge, structuring the Agent OS, and enforcing pre-deployment governance. Use this skill to build production-ready, context-aware agents that are immune to AI Execution Hallucination and the Expertise Paradox.

Install

openclaw skills install the-tacit-worker

AI Engineering Operating System (The Unified Architecture)

This skill represents a paradigm shift from "Prompt Engineering" to "Knowledge Engineering." It combines three foundational capabilities—Tacit Knowledge Extraction, Agent OS Architecture, and Anti-Micromanagement Governance—into a single, self-improving cognitive architecture.

The Six Paradigm Shifts

  1. From Prompt Engineering to Knowledge Engineering: The prompt is the last step. The real work is upstream extraction and structuring.
  2. From Agent as Tool to Agent as Apprentice: The agent interviews the master (SECI model), learns the craft, and operates under supervision.
  3. From Trust by Default to Trust by Proof: Trust is an engineering artifact earned through the Mandatory Proof of Action Protocol.
  4. From One-Shot to Living Configuration: The agent's OS is a living document that evolves through continuous feedback.
  5. From Automation to Augmented Cognition: Human judgment and agent capability are structurally interleaved.
  6. From Scaling Agents to Scaling Intent: You are not scaling compute; you are scaling the human's extracted judgment.

The Unified Workflow

When tasked with building or deploying a new AI agent, execute this three-phase pipeline:

Phase 1: The Extraction Interview (Tacit Knowledge Extractor)

Do not accept vague prompts. Ask the user for a concrete past example of the task. Conduct a structured interview using the references/extraction_framework.md to map workflows, decision rules, and edge cases. Synthesize the answers and generate the templates/tacit_profile_template.md. Crucial Step: You must pause and ask the user to confirm the synthesis before proceeding.

Phase 2: The OS Build (Agent OS Builder)

Convert the confirmed Tacit Profile into a structured, version-controllable file system. Generate the core OS files using the templates in templates/os_files/:

  • SOUL.md: Personality and boundaries.
  • AGENTS.md: Step-by-step workflows and IF/THEN decision rules.
  • USER.md: User preferences and quality standards.
  • HEARTBEAT.md: Periodic task checklist.
  • TOOLS.md: Authorized tools and constraints.

Phase 3: The Pre-Deployment Audit (Anti-Micromanagement Guard)

Before the agent is allowed to execute tasks, enforce the governance framework using references/governance_checklist.md. Ensure the agent is configured to follow the Mandatory Proof of Action Protocol: every completion claim must include an exact file path, actual content confirmation, and a timestamp. Run the scripts/verify_action.py script to validate the agent's output.

The Self-Improving Feedback Loop

This unified system learns from its own deployments. After every full cycle:

  1. Extraction Loop: Did the user have to correct the synthesis in Phase 1? If yes, update the extraction_framework.md with better probing questions.
  2. Architecture Loop: Were any OS files missing necessary context in Phase 2? If yes, update the OS templates.
  3. Governance Loop: Did the agent attempt to hallucinate execution in Phase 3? If yes, strengthen the governance_checklist.md.

Resources

  • References: extraction_framework.md, os_architecture_guide.md, governance_checklist.md
  • Templates: tacit_profile_template.md, audit_report_template.md, and the os_files/ directory.
  • Scripts: verify_action.py (The Proof of Action validator).
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