CertainLogic Stack is an Openclaw Skills AI stack that combines verified knowledge, low-cost routing, caching, and audit trails to cut spend and stop hallucinations.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install certainlogic-stack
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install certainlogic-stack using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is CertainLogic Stack?
CertainLogic Stack is a production-ready AI stack for teams using Openclaw Skills who need lower token spend, fewer hallucinations, and verifiable agent behavior. It ships as one install with four coordinated components: Company Brain Core OS for deterministic verified answers, Token Reduction Engine (TRE) for intelligent caching and intent protection, AgentPathfinder for HMAC-SHA256 audit trails, and Smart Router for choosing the cheapest capable model for each request.
The result is an AI workflow that answers from trusted facts when it can, routes to low-cost models when it should, and records what happened every step of the way. That makes CertainLogic Stack especially valuable for Openclaw Skills deployments where cost control, compliance, and operational transparency matter.
CertainLogic Stack Use Cases
- Building AI assistants that must answer from verified company knowledge instead of free-form LLM guesses.
- Reducing token bills on repeated prompts, support questions, or internal lookup workflows.
- Routing coding and architecture prompts to the cheapest capable model without manual switching.
- Adding tamper-evident audit logs for tool calls, success/failure detection, and compliance reviews.
- Protecting agents from dangerous or wasteful intents before a model is invoked.
- Standardizing Openclaw Skills workflows that need measurable latency, accuracy, and cost savings.
How CertainLogic Stack Works
- Install the stack with
clawhub, then generatestack-config.jsonand verify component health. - A user or agent submits a query through the stack.
- LLM Intent Protection screens for dangerous, wasteful, or unsupported requests before model spend occurs.
- TRE checks the cache; warm hits return in about 8ms with zero token cost, while misses continue downstream.
- Smart Router selects the cheapest capable model for the task, or Company Brain serves verified facts when the answer exists in the knowledge base.
- Hallucination Guard prevents uncertain outputs from being stored, and AgentPathfinder writes a tamper-evident HMAC-SHA256 audit record for every tool call.
- The stack returns the response plus a persistent log, giving you traceability, cost control, and measurable performance.
CertainLogic Stack Setup
- Install prerequisites: Python 3.8+ and the
clawhubCLI. - Run the one-click installer:
clawhub install certainlogic-stack && cd certainlogic-stack && bash setup.sh
- If you want manual control, install each component:
clawhub install company-brain-os
clawhub install certainlogic-tre
clawhub install certainlogic-pathfinder
clawhub install smart-router-coding
clawhub install smart-router-intents
- Verify the install and generated configuration:
cd certainlogic-stack && python3 test.py
CertainLogic Stack Data Schema & Taxonomy
CertainLogic Stack organizes runtime data around four core domains and one generated config file.
| Artifact / Namespace | Contents | Purpose |
|---|---|---|
stack-config.json |
Generated by setup.sh after install |
Stores component wiring, local settings, and runtime preferences. |
| Company Brain knowledge base | Verified facts, canonical company answers, and approved policy data | Returns deterministic answers without an LLM call. |
| TRE cache | Cache keys, cached answers, hit/miss status, latency, and savings metadata | Serves repeat queries quickly and cheaply. |
| Smart Router metadata | Intent label, model choice, cost tier, and routing reason | Selects the cheapest capable model for each request. |
| AgentPathfinder audit records | Tool call name, inputs, outputs, execution status, duration, and HMAC-SHA256 signature | Produces tamper-evident proof of agent activity. |
Metadata taxonomy
verified_fact: approved knowledge stored by Company Braincache_hit/cache_miss: TRE response stateintent_safe/intent_blocked: LLM Intent Protection decisionmodel_route: router-selected model and why it was chosentool_call: each audited action performed by an agentaudit_signature: HMAC-SHA256 integrity markerperformance_metric: latency, hit rate, token reduction, and accuracy
CertainLogic Stack Advanced Features
- Deterministic answer paths for core facts, reducing hallucinations to near zero on known data.
- TRE-powered intelligent caching with warm hits around 8ms and 60-85% token cost reduction on repeat traffic.
- LLM Intent Protection that blocks dangerous or wasteful prompts before model spend happens.
- Smart Router decisions in about 2ms to send each prompt to the cheapest capable model.
- HMAC-SHA256 audit trails on every tool call for compliance, debugging, and tamper-evident logging.
- Component-by-component verification so Openclaw Skills teams can test Company Brain, TRE, and Pathfinder independently.
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