Home / ScenarioGrid / ScenarioGrid Specification
ScenarioGrid
Trace the logic.
ScenarioGrid is an open source specification for structured AI reasoning based on IF/THEN scenarios. It provides a modular framework for reviewing information, evaluating conditions, analyzing evidence and contributors, tracing sources and provenance, identifying contradictions, assessing potential consequences, and determining logical next steps.
ScenarioGrid is designed to make AI reasoning more transparent, auditable, and human controlled. Instead of producing an unexplained conclusion, ScenarioGrid requires the reasoning path to be traceable from the available evidence through the conditions being evaluated, the applicable IF/THEN logic, and the resulting conclusion or next step.
Purpose
ScenarioGrid provides a structured method for answering questions such as:
- What is known?
- What evidence supports what is known?
- What additional information is available?
- What does each piece of evidence indicate?
- What conditions exist?
- If a condition is true, what follows?
- If a condition is false, what changes?
- What contradictions or uncertainties exist?
- Who contributed relevant information?
- What sources support each conclusion?
- What are the foreseeable consequences?
- What is the most logical next step?
The specification is intended for complex reasoning where conclusions should be based on traceable evidence rather than unsupported assumptions.
Core Principles
Evidence Driven Reasoning
ScenarioGrid requires reasoning to be grounded in available evidence. Information should be identified, evaluated, connected to relevant conditions, and preserved as part of the reasoning record.
Conditional Logic
ScenarioGrid uses IF/THEN reasoning to evaluate how different conditions affect possible conclusions and next steps. Each meaningful condition should be capable of producing a distinct logical path.
Traceable Reasoning
Every significant conclusion should have an identifiable reasoning path connecting evidence, interpretation, conditions, logic, and outcome.
Provenance Preservation
Sources, contributors, timestamps, references, and relevant origin information should remain associated with the evidence and conclusions they support.
Contradiction Awareness
Conflicting information must be identified and evaluated rather than silently resolved or discarded.
Human Control
ScenarioGrid does not treat a logical conclusion as automatic authorization to act. Human review may be required before consequential action is taken.
Do No Harm
Safety and foreseeable consequences are fundamental to ScenarioGrid. The system must evaluate potential harm before recommending consequential next steps and should prefer safer alternatives when appropriate.
Modular Design
ScenarioGrid is modular by design. Core reasoning capabilities are defined as independent modules that can be implemented, replaced, extended, or improved without requiring the entire specification to be redesigned.
Core Modules
Scenario Definition Module
Defines the scenario being evaluated, including the question, objective, scope, known conditions, relevant entities, constraints, and desired outcome.
The module establishes the boundaries of the reasoning process and prevents unrelated information from being incorporated without justification.
Archive Intelligence Module
Reviews available archived information surrounding the scenario.
The module identifies historical records, previously collected evidence, prior conclusions, earlier decisions, relevant documents, and other available information that may affect the current reasoning process.
Deep Search Module
Expands the information available to the reasoning process when existing material is insufficient.
The module can identify additional relevant sources, investigate unresolved questions, search for corroborating evidence, and locate information needed to evaluate competing conditions.
Evidence Extraction Module
Extracts relevant facts, claims, observations, statements, measurements, findings, and other evidence from reviewed material.
Each extracted item should remain connected to its source and context.
Point by Point Review Module
Evaluates relevant information individually before combining it into broader conclusions.
The module is intended to reduce the risk of overlooking important details by requiring material evidence to be examined rather than relying exclusively on generalized summaries.
Contributor Analysis Module
Analyzes the work and contributions of relevant people, organizations, researchers, authors, systems, or other contributors.
The module preserves contributor attribution and evaluates how individual contributions affect the overall body of evidence.
IF/THEN Logic Module
Converts identified conditions into explicit logical branches.
The module evaluates statements such as:
IF condition A is true, THEN outcome B follows.
IF condition A is false, THEN outcome C may follow.
Multiple conditions may be combined to create more complex reasoning paths.
Conflict and Contradiction Module
Identifies conflicting claims, inconsistent evidence, incompatible conditions, and competing interpretations.
The module records the conflict, identifies the sources involved, evaluates available evidence, and prevents unresolved contradictions from being presented as established facts.
Provenance Module
Maintains the origin and history of evidence throughout the reasoning process.
Provenance may include source identity, contributor, document, location within a source, retrieval information, timestamp, transformation history, and relationships between original evidence and derived conclusions.
Confidence and Evidence Module
Evaluates the strength and reliability of conclusions based on available evidence.
Confidence should reflect factors such as evidence quality, corroboration, contradictions, completeness, source reliability, uncertainty, and unresolved questions.
Reasoning Chain Module
Maintains the complete logical path from evidence to conclusion.
A reasoning chain should make it possible to identify the evidence considered, interpretation applied, condition evaluated, logical branch followed, assumptions introduced, uncertainty identified, and conclusion reached.
Do No Harm Module
Evaluates foreseeable risks and potential harm associated with proposed conclusions and next steps.
The module is mandatory and cannot be disabled as an optional feature.
When a proposed next step presents unacceptable foreseeable harm, ScenarioGrid should not recommend that step as the default outcome. It should identify the relevant risk, explain the concern, identify uncertainty where applicable, and consider safer alternatives, additional information gathering, or human review.
Next Step Module
Determines the most logical next step based on the completed reasoning process.
A next step may include taking action, gathering additional information, investigating a contradiction, requesting clarification, seeking human review, selecting a safer alternative, or taking no action.
Human Review Module
Provides mechanisms for human examination of reasoning, evidence, assumptions, risks, and conclusions.
Human review should be available whenever uncertainty, conflicting evidence, significant consequences, or safety concerns make automated progression inappropriate.
Decision Record Module
Preserves the final reasoning outcome as an auditable record.
A decision record should include the scenario, evidence reviewed, sources, contributors, conditions, logical branches, contradictions, assumptions, confidence, risks, human review status, conclusion, and recommended next step.
Optional Plugin Modules
ScenarioGrid supports optional plugin modules that extend the core specification without changing its fundamental reasoning model.
Knowledge Graph Plugin
Connects evidence, contributors, entities, conditions, sources, and conclusions through structured relationships.
Academic Research Plugin
Provides specialized handling for academic publications, research findings, citations, studies, and scholarly evidence.
Legal Research Plugin
Supports jurisdiction-specific legal research, statutes, regulations, cases, legal authorities, citations, and legal reasoning.
Statistical Analysis Plugin
Provides statistical evaluation of evidence, probabilities, distributions, correlations, trends, and uncertainty.
Timeline Analysis Plugin
Organizes evidence and events chronologically to identify sequences, dependencies, changes, and temporal relationships.
Citation Verification Plugin
Verifies citations and evaluates whether cited material supports the claims associated with it.
Source Reputation Plugin
Evaluates characteristics of sources that may affect their evidentiary value while preserving the distinction between source evaluation and factual evidence.
Document Intelligence Plugin
Analyzes large collections of documents and identifies relevant passages, relationships, entities, claims, and evidence.
Simulation Plugin
Evaluates hypothetical scenarios by modeling potential conditions, outcomes, dependencies, and consequences.
Forecasting Plugin
Uses available evidence and defined assumptions to evaluate potential future outcomes while clearly separating forecasts from established facts.
Multi Agent Review Plugin
Allows multiple independent reasoning processes to evaluate the same scenario and compare their findings.
Adversarial Review Plugin
Attempts to identify weaknesses, unsupported assumptions, contradictory evidence, alternative explanations, and potential failure points in a reasoning chain.
Consensus Analysis Plugin
Compares conclusions across contributors, sources, reasoning processes, or independent evaluations to identify agreement and disagreement.
Memory Plugin
Provides controlled access to relevant historical reasoning records while preserving provenance and allowing users to determine what information may be reused.
Federation Plugin
Allows independent ScenarioGrid implementations to exchange compatible evidence, reasoning records, and conclusions while maintaining provenance and governance controls.
Visualization Plugin
Presents scenarios, conditions, evidence, reasoning chains, contradictions, and possible outcomes through visual representations.
Audit Plugin
Provides expanded auditing capabilities for reviewing reasoning history, evidence changes, source changes, human interventions, and system outputs.
Evidence Requirements
ScenarioGrid should distinguish between evidence, interpretation, assumption, inference, and conclusion.
Evidence should remain connected to its source whenever possible. Interpretations should not be represented as original evidence. Assumptions should be explicitly identified. Inferences should identify the evidence and conditions from which they were derived.
When evidence is incomplete, ScenarioGrid should identify what is missing rather than treating absence of evidence as evidence of a particular conclusion.
IF/THEN Processing
ScenarioGrid evaluates scenarios through explicit conditional branches.
Each branch should identify:
- The condition being evaluated
- The evidence relevant to the condition
- The source of that evidence
- The interpretation applied
- The resulting logical state
- The next applicable condition
- The resulting conclusion or next step
- Relevant risks and potential harms
- Confidence and uncertainty
- Unresolved questions
A scenario may contain multiple branches, and each branch should remain independently traceable.
Research Process
ScenarioGrid should begin with the information already available to it before expanding the search.
The reasoning process should:
- Define the scenario
- Identify relevant archived information
- Review available evidence
- Identify missing information
- Conduct additional research when necessary
- Extract relevant evidence
- Review evidence point by point
- Analyze contributors and sources
- Identify contradictions
- Evaluate conditions
- Apply IF/THEN logic
- Assess confidence and uncertainty
- Evaluate foreseeable harm
- Determine logical next steps
- Preserve the complete reasoning record
- Provide human review when appropriate
Source and Provenance Requirements
ScenarioGrid should preserve sufficient provenance to allow users to understand where important information originated and how it was used.
A conclusion should not be presented as independently established when its basis depends upon a particular source, contributor, assumption, or inference.
When sources disagree, the disagreement should remain visible within the reasoning record.
Consequence Evaluation
Logical possibility does not automatically establish that an action should be taken.
ScenarioGrid should evaluate foreseeable consequences before recommending consequential next steps. Where an alternative can achieve a comparable objective with substantially lower foreseeable risk, the safer alternative should be considered.
Doing nothing, gathering additional information, or requesting human review may be the most logical next step.
Specification Branding License (SBL)
Standard
- Fully AGPL-3.0+ compliant system
- Copyleft enforced for network deployments
- Required attribution:
- Roxanne Ardary
- https://www.roxanneardary.com/
Optional
- Specification Branding License (SBL)
- Attribution-free commercial deployment
- Pricing based on scale, usage, and deployment scope
- https://roxanneardary.com/scenariogrid/
License & Notice Requirements
ScenarioGrid is released under the GNU Affero General Public License v3.0 or later (AGPL-3.0+).
By contributing to any Open Arsenal project, you agree that your contributions will also be released under this license.
Please note the following:
- All contributions must comply with the AGPL-3.0+ terms.
- Under Section 7 of the license, all redistributions, forks, and derivative works must preserve attribution to: Roxanne Ardary and roxanneardary.com.
- ScenarioGrid specifications are free to use with attribution. A Specification Branding License can be negotiated upon request.
- The project’s notice.md file tracks attribution requirements and contributor acknowledgments. Any update that adds new contributors or modifies attribution should also update
notice.md. - When submitting a pull request, ensure that any new files maintain the attribution headers where applicable.
- Network-deployed versions of this software must also remain fully AGPL-3.0+ compliant, including exposure of source code modifications when applicable under the license.
For full legal details, please refer to the AGPL-3.0+ license and the project’s notice.md file. notice.md file.
Notice – ScenarioGrid
Attribution Requirement: Under Section 7 of the AGPL 3.0+ license, all redistributions, forks, and derivative works, including network-deployed versions of this project, must provide attribution to Roxanne Ardary and roxanneardary.com.
Contributors
This file tracks contributors and their specific contributions to the project.
- Roxanne Ardary, roxanneardary.com – September 9, 2026
Created the repository for ScenarioGrid, an open source AI reasoning specification for analyzing evidence, evaluating IF/THEN scenarios, tracing provenance, identifying contradictions, and determining logical next steps. - [Add other contributors here] – [Date]
[Describe contribution in one sentence]
License – ScenarioGrid
This repository is licensed under the GNU Affero General Public License v3.0 or later (AGPL-3.0+).
Key Points:
- You are free to use, modify, and distribute the code.
- All redistributions, forks, and derivative works or network-deployed versions must also be licensed under AGPL-3.0+ and provide attribution to Roxanne Ardary and roxanneardary.com as required under Section 7 of the license.
- The software is provided “as is,” without warranty of any kind.
For the full license text, see GNU AGPL-3.0 License.