Analysis Templates

Analysis Templates

The Analysis Templates represent the core analytical frameworks of the Claude Sleuth toolkit. These templates transition the investigation from raw data collection into structured intelligence by enforcing rigorous methodologies such as the POLE (Person, Object, Location, Event) schema, the ACH (Analysis of Competing Hypotheses) matrix, and UTC-normalized chronological mapping.

These templates are assembled into the investigator's workspace by the template_builder.py utility, drawing from the skills/claude-sleuth/templates/analysis/ directory.

1. POLE Entity Extraction (pole.md)

The POLE template implements the primary ontological framework for Step 6 (Structured Extraction). It is designed to parse unstructured text—such as witness statements, scraped web data, or investigative notes—into a machine-readable format.

Implementation & Data Flow

The template enforces a strict schema for four canonical entities:

• Person: Requires givenName, familyName, birthDate, and unique identifiers (e.g., Passport, DUNS).
• Object: Digital assets, vehicles, or physical items.
• Location: Physical addresses or coordinates.
• Event: Specific occurrences tied to a timestamp.

Data extracted via this template flows into the Entity Resolution (ER) Pipeline, which utilizes the Fellegi-Sunter framework for probabilistic record linkage.

Code Entity Mapping: Extraction to Resolution

The following diagram illustrates how natural language entities are transformed into code-level objects within the system.

Diagram: Entity Extraction and Resolution Flow

graph TD
    subgraph "Natural Language Space"
        A["Unstructured Text/Notes"]
    end

    subgraph "Template Entity Space (pole.md)"
        B["Person Record"]
        C["Object Record"]
        D["Location Record"]
        E["Event Record"]
    end

    subgraph "Code Entity Space (entity_resolver.py)"
        F["Fellegi-Sunter Matcher"]
        G["Candidate Match List"]
        H["CSDb 'entities' Table"]
    end

    A -->| "Task 6.2 Parsing" | B
    A -->| "Task 6.2 Parsing" | C
    B -->| "Task 7.1 Probabilistic Linkage" | F
    F -->| "Confidence Threshold" | G
    G -->| "Manual/Auto Resolution" | H

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2. Chronological Matrix (chronological-matrix.md)

The Chronological Matrix is the "temporal backbone" of the investigation (Step 9). It prevents sequencing errors in multi-jurisdictional cases by mandating UTC normalization for every dated event.

Key Analytical Functions

• Master Chronology Construction: Aggregates all dated events from the evidence register.
• Gap Analysis: Explicitly documents "unknowns" to identify periods of unaccounted activity.
• Conflict Resolution: Compares source reliability (Admiralty Grades) when timestamps for the same event conflict.

3. Network Architecture (network-architecture.md)

This template facilitates Step 10 (Relational Processing) by generating an Edge List. This list is the precursor to Quantitative Social Network Analysis (SNA).

Data Structure

The template requires four mandatory fields for every relationship:

1. Source (Entity A)
2. Target (Entity B)
3. Relationship Type (e.g., "Owned By", "Director Of")
4. Evidence Citation

SNA Metrics

The resulting graph is analyzed for:

• Degree Centrality: To identify "Central Hubs".
• Betweenness Centrality: To identify "Bridge Nodes" acting as gatekeepers.

4. ACH Matrix (ach.md)

The Analysis of Competing Hypotheses (ACH) template is the primary tool for Phase 5 (Hypothesis Reasoning). It operates on the Inconsistency Principle: the most likely explanation is the one with the fewest inconsistencies against the evidence.

Implementation Requirements

• Exclusivity: The matrix must evaluate at least three mutually exclusive hypotheses.
• Diagnosticity: Analysts score evidence based on how well it distinguishes between hypotheses.
• Traceability: Every evidence item in the matrix must retain its Admiralty 6x6 grade from Phase 2.

5. Verification & Morphological Templates

These specialized templates ground the investigation in physical and digital reality (Step 11).

Template	Analytical Framework	Key Outputs
verification.md	Map Regression	Historical landscape changes, chronolocation via shadows/weather.
morphological.md	Spatial Econometrics	Significance assessments of regional economies and site evolution.

Verification Logic Flow

The following diagram maps the verification process from visual evidence to the structured report.

Diagram: Media Authentication and Spatial Analysis

graph LR
    subgraph "Input Space"
        IMG["Raw Image/Video"]
        MAP["Historical Maps"]
    end

    subgraph "Analysis Scripts (scripts/)"
        V_SC["evidence_preservation.py"]
        G_SC["geolocation.py"]
    end

    subgraph "Analysis Templates (templates/analysis/)"
        VER["verification.md"]
        MOR["morphological.md"]
    end

    IMG --> V_SC
    V_SC -->| "SHA-256 Hash" | VER
    IMG --> G_SC
    G_SC -->| "EXIF/Visual Cues" | VER
    MAP -->| "Regression Analysis" | MOR
    VER -->| "Authentication" | OUT["Final Briefing"]

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