SCM Exploration Template
Date: 2025-04-23
Purpose
This document provides the standardized template for all Strategic Curiosity Mode (SCM) explorations in Operation Foresight. Using this consistent format ensures thorough documentation of triggers, methodology, and findings while facilitating seamless integration into the main research flow.
Template Task ID: scm_template_001 | Status: Active
Strategic Curiosity Mode serves as a cognitive safety mechanism that enables exploration of edge cases, anomalies, and unexpected patterns that might otherwise be overlooked in linear research. Each SCM exploration should be documented according to this template and stored in the projects/operation_foresight/scm/explorations/ directory.
📄 SCM Exploration Document Structure
Example:
scm_exploration_anomaly_001.md
1. Frontmatter
Each exploration document begins with YAML frontmatter that includes essential metadata about the trigger and exploration status. This enables efficient tracking, categorization, and retrieval of explorations.
Format: scm_trigger_[category-abbreviation]_[sequential-number]
Example: scm_trigger_an_001
One of: anomaly, gap, combinatorial, emergence, meta
ISO date format: YYYY-MM-DD
Number 0-5 corresponding to research phases
One of: active, completed, integrated, archived
📝 Content Sections
2. Trigger Context
Provide a clear, concise description of what triggered the SCM activation. This should include specific observations, data points, or patterns that met the activation threshold for one of the trigger categories.
Example: "During analysis of recent AI security incidents reported in Q1 2025, we observed that 23% of successful attacks utilized techniques that don't fit within any of the current attack typologies in our threat framework. This exceeds the 20% threshold for meta-analysis triggers and suggests a potential blindspot in our analytical framework."
3. Exploration Questions
List the specific questions that this SCM exploration aims to investigate. These questions should be focused, concrete, and designed to explore the implications, causes, or characteristics of the triggering observation.
Example:
- What common characteristics exist among the attacks that don't fit current typologies?
- Are these novel attacks driven by technical innovation or by new combinations of existing techniques?
- What modifications to our threat framework would be required to categorize these attacks?
- Does this pattern suggest the emergence of a fundamentally new threat vector?
4. Methodology
Detail the cognitive process sequence and specific investigative approaches used for this exploration. Reference specific logic primitives and process combinations from the cognitive process library.
Example: "This exploration utilized the 'Pattern Recognition' cognitive process (Observe → Infer), followed by 'Comparative Analysis' (Observe → Define → Reflect → Infer → Synthesize). We first analyzed the 23 anomalous attacks to identify common features, then compared them with our existing threat taxonomy to identify specific gaps and potential modifications."
5. Findings
Present the results of the exploration, explicitly categorizing findings based on the confidence level and evidence strength. Always maintain clear separation between different confidence levels.
Example:
Confirmed Findings:
- 18 of the 23 anomalous attacks (78%) utilized techniques that combine elements from multiple existing attack categories
- Current threat taxonomy lacks a formal way to represent hybrid or composite attack patterns
Plausible Findings:
- The increase in hybrid attacks may be driven by the proliferation of automated attack generation tools
- Taxonomic constraints are limiting threat detection capabilities in existing security systems
Speculative Findings:
- Future attacks may involve increasingly complex combinations, potentially evolving toward "attack swarms" with multiple simultaneous hybrid vectors
- AI-based threat classification may require graph-based rather than hierarchical taxonomies
6. Integration Recommendation
Provide specific recommendations for how the findings should be integrated into the main research flow. Reference specific documents, sections, or frameworks that should be updated.
Example:
"We recommend the following integration approach:
- Direct Incorporation: Update the Threat Vector Profiles document to include a new section on "Hybrid Attack Patterns" that incorporates the confirmed findings
- Framework Modification: Modify the threat taxonomy in the Framework document to add support for composite attack vectors and cross-category combinations
- Appendix Inclusion: Add the speculative findings about potential evolution toward attack swarms in the Appendix of the Second-Order Effects document, clearly marked as speculative but worthy of monitoring
This integration should be completed before Phase 3 to ensure all subsequent analysis incorporates the updated taxonomy."
Full Template for Copy/Paste
Best Practices for SCM Exploration Documentation
- Precision in Trigger Description: Be specific about what triggered the SCM activation, including exact measurements, thresholds, and context. Vague descriptions make it difficult to evaluate the validity of the exploration.
- Clear Confidence Labeling: Maintain rigorous separation between confirmed, plausible, and speculative findings. This is essential for responsible integration into the main research.
- Methodological Transparency: Explicitly reference the cognitive processes and methodological approaches used. This allows others to understand how conclusions were reached.
- Exploration Scope Control: Keep SCM explorations focused on the specific trigger. Avoid scope creep that could dilute the investigation or consume excessive resources.
- Integration Specificity: Provide concrete, actionable integration recommendations that specify exactly which documents should be updated and how.
- Traceability: Ensure that all SCM explorations are properly logged in the trigger log and that integration decisions are documented in the integration decisions registry.
- Time Bounding: SCM explorations should be time-bounded (default: 20% of phase resources) to prevent infinite exploration loops. Document time usage in the methodology section.