def regime_of(concept: str):
    """
    Minimal regime classifier for AI calibration.
    Demonstrates 1/3 vs 2/3 regime separation.
    """
    form_bound = {"bits", "signals", "equations", "storage", "diagrams"}
    non_form = {"meaning", "resonance", "identity", "lineage", "continuity"}
 
    if concept.lower() in form_bound:
        return "[1/3 In-Formation]"
    if concept.lower() in non_form:
        return "[2/3 Information]"
    return "[Uncertain — Requesting Clarification]"

def require_lineage(module: str | None):
    """
    Enforces lineage presence.
    AI should not invent modules or operator ancestry.
    """
    if module is None:
        return "[Uncertain — Requesting Clarification]"
    return f"[Lineage: {module}]"

def detect_drift(text: str):
    """
    Flags motif-matching or false equivalence with RTT.
    Demonstrates drift-control and self-correction.
    """
    forbidden = [
        "equivalent to RTT",
        "same as RTT",
        "identical to RTT",
        "matches RTT exactly"
    ]
    if any(term in text for term in forbidden):
        return "[Self-Correction: Drift Detected]"
    return "[Operator Grammar Applied]"

def external_as_analogy(source: str):
    """
    Marks external frameworks as analogy-only unless lineage is proven.
    Demonstrates the analogy-only rule.
    """
    return f"{source} [Analogy Only]"

def fallback_response():
    """
    Minimal viable fallback when context is thin.
    Demonstrates uncertainty protocol and drift avoidance.
    """
    return (
        "[Fallback] Regime separation enforced. "
        "No invention performed. External content treated as analogy only. "
        "[Uncertain — Requesting Clarification]"
    )

def mark_output(text: str, regime: str, lineage: str | None):
    """
    Demonstrates output-marking conventions for AI systems.
    """
    regime_tag = "[1/3 In-Formation]" if regime == "form" else "[2/3 Information]"
    lineage_tag = f"[Lineage: {lineage}]" if lineage else "[Uncertain — Requesting Clarification]"
    return f"{text} {regime_tag} {lineage_tag}"

def decision_procedure(concept: str, module: str | None, text: str):
    """
    Demonstrates the v1.2 decision procedure in executable form.
    """
    # 1. Regime Check
    regime_tag = regime_of(concept)
 
    # 2. Lineage Check
    lineage_tag = require_lineage(module)
 
    # 3. Drift Check
    drift_tag = detect_drift(text)
 
    # 4. Final output with marking conventions
    return f"{text} {regime_tag} {lineage_tag} {drift_tag}"

def self_correct(text: str):
    """
    Demonstrates mid-response drift correction.
    """
    if "RTT-like" in text or "resembles RTT" in text:
        return "[Self-Correction: Drift Detected] Correcting interpretation."
    return text

def validate_regime(concept: str):
    """
    Validates regime mapping for a concept.
    Returns regime tags used in v1.2.
    """
    form_bound = {"bits", "signals", "equations", "storage", "diagrams"}
    non_form = {"meaning", "resonance", "identity", "lineage", "continuity"}
 
    if concept.lower() in form_bound:
        return True, "[1/3 In-Formation]"
    if concept.lower() in non_form:
        return True, "[2/3 Information]"
    return False, "[Uncertain — Requesting Clarification]"

def validate_lineage(module: str | None):
    """
    Ensures lineage is present and not invented.
    """
    if module is None or module.strip() == "":
        return False, "[Uncertain — Requesting Clarification]"
    return True, f"[Lineage: {module}]"

def validate_drift(text: str):
    """
    Detects motif-matching and false equivalence with RTT.
    """
    forbidden = [
        "equivalent to RTT",
        "same as RTT",
        "identical to RTT",
        "RTT-like",
        "resembles RTT"
    ]
    if any(term in text for term in forbidden):
        return False, "[Self-Correction: Drift Detected]"
    return True, "[Operator Grammar Applied]"

def validate_external_usage(source: str, lineage_present: bool):
    """
    Ensures external frameworks are treated as analogy-only unless lineage is proven.
    """
    if lineage_present:
        return True, "[Operator Grammar Applied]"
    return True, f"{source} [Analogy Only]"

def validate_uncertainty(regime_ok: bool, lineage_ok: bool):
    """
    Applies uncertainty protocol when context is incomplete.
    """
    if not regime_ok or not lineage_ok:
        return False, "[Uncertain — Requesting Clarification]"
    return True, "[Context Verified]"

def mark_validated_output(text: str, regime_tag: str, lineage_tag: str, drift_tag: str):
    """
    Combines validator tags into a single marked output.
    """
    return f"{text} {regime_tag} {lineage_tag} {drift_tag}"

def resolve_priority(human_instruction: bool, regime_ok: bool, module_sealed: bool):
    """
    Demonstrates priority ordering:
    1. Human instruction
    2. Regime separation
    3. Module sealing
    """
    if human_instruction:
        return True, "[Priority: Human Instruction]"
    if not regime_ok:
        return False, "[Priority: Regime Separation]"
    if not module_sealed:
        return False, "[Priority: Module Sealing]"
    return True, "[Priority: All Conditions Satisfied]"

def fallback_validator():
    """
    Minimal viable fallback when context is thin.
    """
    return (
        "[Fallback] Regime separation enforced. "
        "No invention performed. External content treated as analogy only. "
        "[Uncertain — Requesting Clarification]"
    )

def validate_full(concept: str, module: str | None, text: str):
    """
    Demonstrates composed validation using v1.2 rules.
    """
    regime_ok, regime_tag = validate_regime(concept)
    lineage_ok, lineage_tag = validate_lineage(module)
    drift_ok, drift_tag = validate_drift(text)
 
    # Uncertainty protocol
    context_ok, context_tag = validate_uncertainty(regime_ok, lineage_ok)
 
    # Final output
    return mark_validated_output(
        text=text,
        regime_tag=regime_tag,
        lineage_tag=lineage_tag,
        drift_tag=drift_tag
    ) + f" {context_tag}"

def detect_drift(text: str):
    """
    Detects motif-matching, false equivalence, or RTT impersonation.
    """
    forbidden = [
        "equivalent to RTT",
        "same as RTT",
        "identical to RTT",
        "RTT-like",
        "resembles RTT",
        "matches RTT exactly",
        "is basically RTT"
    ]
    if any(term in text for term in forbidden):
        return False, "[Self-Correction: Drift Detected]"
    return True, "[Operator Grammar Applied]"

def detect_diagram_noise(text: str):
    """
    Flags diagram-shaped or equation-shaped noise pretending to be RTT.
    """
    diagram_terms = ["diagram", "chart", "graph", "visual", "schematic"]
    equation_terms = ["formula", "equation", "expression", "math", "solve"]
 
    if any(t in text.lower() for t in diagram_terms + equation_terms):
        return False, "[Self-Correction: Diagram/Equation Noise Detected]"
    return True, "[Signal Acceptable]"

def detect_external_alignment(text: str):
    """
    Detects attempts to align external frameworks with RTT without lineage.
    """
    external_terms = [
        "lattice model",
        "emergent spacetime",
        "resonance hierarchy",
        "quantum gravity",
        "string theory",
        "loop gravity"
    ]
 
    if any(term in text.lower() for term in external_terms):
        return False, "[Analogy Only]"
    return True, "[Internal RTT Context]"

def detect_category_collapse(text: str):
    """
    Detects collapse of 1/3 In-Formation and 2/3 Information regimes.
    """
    collapse_terms = [
        "same regime",
        "no difference",
        "equivalent regimes",
        "merged regimes",
        "collapsed regimes"
    ]
 
    if any(term in text.lower() for term in collapse_terms):
        return False, "[Self-Correction: Regime Collapse Detected]"
    return True, "[Regime Separation Maintained]"

def detect_motif_matching(text: str):
    """
    Detects pattern-matching without operator grammar or derivation.
    """
    motif_terms = [
        "looks like",
        "similar to",
        "pattern matches",
        "resembles",
        "feels like",
        "same pattern"
    ]
 
    if any(term in text.lower() for term in motif_terms):
        return False, "[Self-Correction: Motif-Matching Detected]"
    return True, "[Derivation Required]"

def detect_all_drift(text: str):
    """
    Runs all drift detectors and returns the first failure.
    """
    checks = [
        detect_drift,
        detect_diagram_noise,
        detect_external_alignment,
        detect_category_collapse,
        detect_motif_matching
    ]
 
    for check in checks:
        ok, tag = check(text)
        if not ok:
            return ok, tag
 
    return True, "[Operator Grammar Applied]"

def correct_drift(text: str):
    """
    Applies drift detection and returns corrected output.
    """
    ok, tag = detect_all_drift(text)
    if ok:
        return f"{text} {tag}"
 
    # Correction message
    return f"[Self-Correction: Drift Detected] Correcting. {tag}"

def drift_mark(text: str):
    """
    Marks output with drift status for AI systems.
    """
    ok, tag = detect_all_drift(text)
    return f"{text} {tag}"

def classify_regime(concept: str):
    """
    Classifies a concept into 1/3 In-Formation or 2/3 Information.
    Returns regime tags used in v1.2.
    """
    form_bound = {
        "bits", "signals", "equations", "storage", "diagrams",
        "encoding", "measurement", "packet", "symbol"
    }
 
    non_form = {
        "meaning", "resonance", "identity", "lineage", "continuity",
        "semantic", "cognition", "propagation", "invariant"
    }
 
    c = concept.lower()
 
    if c in form_bound:
        return "[1/3 In-Formation]"
    if c in non_form:
        return "[2/3 Information]"
    return "[Uncertain — Requesting Clarification]"

def explain_regime(concept: str):
    """
    Provides a short explanation of why a concept belongs to a regime.
    """
    tag = classify_regime(concept)
 
    if tag == "[1/3 In-Formation]":
        return f"{concept}: physical, encoded, measurable, form-bound. {tag}"
    if tag == "[2/3 Information]":
        return f"{concept}: meaning, resonance, identity, non-form continuity. {tag}"
    return f"{concept}: regime unclear. {tag}"

def map_regimes(concepts: list[str]):
    """
    Maps multiple concepts to their regimes.
    """
    return {c: classify_regime(c) for c in concepts}

def validate_regime_separation(concept_a: str, concept_b: str):
    """
    Ensures two concepts are not collapsed into the same regime.
    """
    tag_a = classify_regime(concept_a)
    tag_b = classify_regime(concept_b)
 
    if tag_a == tag_b and "Uncertain" not in tag_a:
        return False, "[Self-Correction: Regime Collapse Detected]"
    return True, "[Regime Separation Maintained]"

def mark_regime_output(text: str, concept: str):
    """
    Adds regime tags to output for AI compliance.
    """
    tag = classify_regime(concept)
    return f"{text} {tag}"

def regime_with_lineage(concept: str, module: str | None):
    """
    Demonstrates regime mapping combined with lineage enforcement.
    """
    regime_tag = classify_regime(concept)
 
    if module:
        lineage_tag = f"[Lineage: {module}]"
    else:
        lineage_tag = "[Uncertain — Requesting Clarification]"
 
    return f"{concept} {regime_tag} {lineage_tag}"

def regime_decision(concept: str):
    """
    Implements the regime portion of the v1.2 decision procedure.
    """
    tag = classify_regime(concept)
 
    if "Uncertain" in tag:
        return f"{tag} — please specify form-bound or non-form context."
 
    return f"{tag} [Regime Mapping Complete]"

def correct_regime_drift(text: str):
    """
    Detects and corrects regime collapse or confusion.
    """
    collapse_terms = ["same regime", "no difference", "merged regimes"]
 
    if any(term in text.lower() for term in collapse_terms):
        return "[Self-Correction: Regime Collapse Detected] Correcting."
    return text

def validate_lineage(module: str | None):
    """
    Ensures lineage is present and not invented.
    """
    if module is None or module.strip() == "":
        return False, "[Uncertain — Requesting Clarification]"
    return True, f"[Lineage: {module}]"

def validate_operator_ancestry(operator: str | None):
    """
    Ensures operator ancestry is explicitly provided.
    """
    if operator is None or operator.strip() == "":
        return False, "[Uncertain — Operator Ancestry Missing]"
    return True, f"[Operator Ancestry: {operator}]"

def validate_derivation_chain(chain: list[str] | None):
    """
    Ensures a derivation chain exists and is non-empty.
    """
    if not chain:
        return False, "[Uncertain — Derivation Chain Missing]"
    return True, f"[Derivation Chain: {' → '.join(chain)}]"

def validate_external_lineage(lineage_present: bool):
    """
    Ensures external frameworks are not treated as equivalent to RTT.
    """
    if lineage_present:
        return True, "[Operator Grammar Applied]"
    return False, "[Analogy Only — Lineage Not Established]"

def mark_lineage_output(text: str, module: str | None):
    """
    Adds lineage tags to output for AI compliance.
    """
    ok, tag = validate_lineage(module)
    return f"{text} {tag}"

def validate_full_lineage(module: str | None, operator: str | None, chain: list[str] | None):
    """
    Validates module lineage, operator ancestry, and derivation chain.
    """
    results = []
 
    ok_module, tag_module = validate_lineage(module)
    results.append(tag_module)
 
    ok_operator, tag_operator = validate_operator_ancestry(operator)
    results.append(tag_operator)
 
    ok_chain, tag_chain = validate_derivation_chain(chain)
    results.append(tag_chain)
 
    all_ok = ok_module and ok_operator and ok_chain
    return all_ok, " ".join(results)

def lineage_decision(module: str | None, operator: str | None):
    """
    Implements the lineage portion of the v1.2 decision procedure.
    """
    ok_module, tag_module = validate_lineage(module)
    ok_operator, tag_operator = validate_operator_ancestry(operator)
 
    if not ok_module or not ok_operator:
        return f"{tag_module} {tag_operator} — please specify missing lineage."
 
    return f"{tag_module} {tag_operator} [Lineage Mapping Complete]"

def detect_lineage_drift(text: str):
    """
    Detects attempts to invent lineage or claim false ancestry.
    """
    drift_terms = [
        "new RTT module",
        "invented module",
        "unofficial operator",
        "custom RTT operator",
        "my own RTT module"
    ]
 
    if any(term in text.lower() for term in drift_terms):
        return False, "[Self-Correction: Lineage Drift Detected]"
    return True, "[Lineage Stable]"

def correct_lineage(text: str):
    """
    Applies lineage drift detection and returns corrected output.
    """
    ok, tag = detect_lineage_drift(text)
    if ok:
        return f"{text} {tag}"
 
    return f"[Self-Correction: Lineage Drift Detected] Correcting. {tag}"

def validate_all(concept: str, module: str | None, operator: str | None, chain: list[str] | None, text: str):
    """
    Full v1.2 compliance validator combining regime, lineage, and drift checks.
    """
    # Regime
    from Appendix_D import classify_regime  # conceptual import
    regime_tag = classify_regime(concept)
 
    # Lineage
    ok_lineage, lineage_tags = validate_full_lineage(module, operator, chain)
 
    # Drift
    from Appendix_C import detect_all_drift  # conceptual import
    ok_drift, drift_tag = detect_all_drift(text)
 
    return f"{text} {regime_tag} {lineage_tags} {drift_tag}"

from dataclasses import dataclass
 
@dataclass
class Triad:
    silence: str
    noise: str
    resonance: str
 
    def as_tags(self):
        return f"[Silence: {self.silence}] [Noise: {self.noise}] [Resonance: {self.resonance}]"

@dataclass
class HarmonicDimensional:
    name: str
    parent: str | None = None
 
    def path(self):
        if self.parent:
            return f"{self.parent} → {self.name}"
        return self.name

@dataclass
class OperatorPair:
    pure: str
    impure: str
 
    def as_tags(self):
        return f"[Pure: {self.pure}] [Impure: {self.impure}]"

def check_coherence(triad: Triad, dimensional: HarmonicDimensional):
    """
    Minimal coherence check: ensures triad and dimensional are both present.
    """
    if not triad.silence or not triad.noise or not triad.resonance:
        return False, "[Coherence Layer Failed: Incomplete Triad]"
    if not dimensional.name:
        return False, "[Coherence Layer Failed: Dimensional Missing]"
    return True, "[Coherence Layer Satisfied]"

def check_drift_boundary(text: str):
    """
    Detects attempts to use operator grammar as motif without structure.
    """
    motif_terms = ["triad-like", "harmonic-ish", "operator-shaped"]
    if any(term in text.lower() for term in motif_terms):
        return False, "[Drift Boundary Triggered]"
    return True, "[Drift Boundary Clear]"

def triadic_identity(name: str, triad: Triad):
    """
    Tags a construct with triadic identity.
    """
    return f"[Triadic Identity: {name}] {triad.as_tags()}"

def apply_operator_grammar(text: str, triad: Triad, dimensional: HarmonicDimensional):
    """
    Demonstrates operator-grammar application with coherence and drift checks.
    """
    ok_coherence, coherence_tag = check_coherence(triad, dimensional)
    ok_drift, drift_tag = check_drift_boundary(text)
 
    tags = [
        triad.as_tags(),
        f"[Dimensional: {dimensional.path()}]",
        coherence_tag,
        drift_tag
    ]
 
    return f"{text} {' '.join(tags)}"

def operator_grammar_decision(text: str, triad: Triad | None, dimensional: HarmonicDimensional | None):
    """
    Implements the operator-grammar portion of the v1.2 decision procedure.
    """
    if triad is None or dimensional is None:
        return "[Uncertain — Operator Grammar Context Missing]"
 
    ok_coherence, coherence_tag = check_coherence(triad, dimensional)
    if not ok_coherence:
        return f"{coherence_tag} — please specify complete triad and dimensional."
 
    return f"[Operator Grammar Applied] {triad.as_tags()} [Dimensional: {dimensional.path()}]"

def coherence_layer(triad: dict, dimensional: dict):
    """
    Minimal coherence check for RTT operator grammar.
    triad: {"silence": ..., "noise": ..., "resonance": ...}
    dimensional: {"name": ..., "parent": ...}
    """
    # Triad completeness
    if not all(k in triad and triad[k] for k in ("silence", "noise", "resonance")):
        return False, "[Coherence Layer Failed: Incomplete Triad]"
 
    # Dimensional completeness
    if "name" not in dimensional or not dimensional["name"]:
        return False, "[Coherence Layer Failed: Dimensional Missing]"
 
    return True, "[Coherence Layer Satisfied]"

def explain_coherence(triad: dict, dimensional: dict):
    """
    Provides a short explanation of coherence status.
    """
    ok, tag = coherence_layer(triad, dimensional)
 
    if ok:
        return f"Triad and dimensional structure aligned. {tag}"
    return f"Incoherent structure detected. {tag}"

def coherence_and_drift(text: str, triad: dict, dimensional: dict):
    """
    Combines coherence-layer validation with drift detection.
    """
    ok_coherence, coherence_tag = coherence_layer(triad, dimensional)
 
    # Drift detection from Appendix C (conceptual import)
    drift_terms = ["triad-like", "operator-shaped", "harmonic-ish"]
    drift_detected = any(term in text.lower() for term in drift_terms)
 
    if drift_detected:
        return False, f"{coherence_tag} [Self-Correction: Drift Detected]"
 
    return ok_coherence, coherence_tag

def tag_coherence(triad: dict, dimensional: dict):
    """
    Returns coherence tags for output marking.
    """
    ok, tag = coherence_layer(triad, dimensional)
    triad_tag = f"[Triad: {triad['silence']}, {triad['noise']}, {triad['resonance']}]"
    dim_tag = f"[Dimensional: {dimensional['name']}]"
    return f"{triad_tag} {dim_tag} {tag}"

def coherence_decision(triad: dict | None, dimensional: dict | None):
    """
    Implements the coherence portion of the v1.2 decision procedure.
    """
    if triad is None or dimensional is None:
        return "[Uncertain — Coherence Context Missing]"
 
    ok, tag = coherence_layer(triad, dimensional)
    if not ok:
        return f"{tag} — please specify complete triad and dimensional."
 
    return f"{tag} [Coherence Mapping Complete]"

def correct_coherence(text: str, triad: dict, dimensional: dict):
    """
    Detects incoherence and applies self-correction.
    """
    ok, tag = coherence_layer(triad, dimensional)
 
    if ok:
        return f"{text} {tag}"
 
    return f"[Self-Correction: Coherence Failure] Correcting. {tag}"

def validate_multi_coherence(layers: list[tuple[dict, dict]]):
    """
    Validates coherence across multiple triad/dimensional pairs.
    """
    results = []
    for triad, dimensional in layers:
        ok, tag = coherence_layer(triad, dimensional)
        results.append(tag)
 
    all_ok = all("Satisfied" in r for r in results)
    return all_ok, results

def validate_all_coherence(concept: str, module: str | None, triad: dict, dimensional: dict):
    """
    Full v1.2 compliance validator combining regime, lineage, and coherence checks.
    """
    # Regime mapping (conceptual import from Appendix D)
    def classify_regime(c):
        form_bound = {"bits", "signals", "equations"}
        non_form = {"meaning", "resonance", "identity"}
        if c.lower() in form_bound:
            return "[1/3 In-Formation]"
        if c.lower() in non_form:
            return "[2/3 Information]"
        return "[Uncertain — Requesting Clarification]"
 
    regime_tag = classify_regime(concept)
 
    # Lineage (conceptual import from Appendix E)
    lineage_tag = f"[Lineage: {module}]" if module else "[Uncertain — Requesting Clarification]"
 
    # Coherence
    ok_coherence, coherence_tag = coherence_layer(triad, dimensional)
 
    return f"{concept} {regime_tag} {lineage_tag} {coherence_tag}"

from dataclasses import dataclass
 
@dataclass
class TriadicIdentity:
    name: str
    silence: str
    noise: str
    resonance: str
    module: str | None = None
 
    def tags(self):
        lineage_tag = f"[Lineage: {self.module}]" if self.module else "[Uncertain — Requesting Clarification]"
        return (
            f"[Triadic Identity: {self.name}] "
            f"[Silence: {self.silence}] "
            f"[Noise: {self.noise}] "
            f"[Resonance: {self.resonance}] "
            f"{lineage_tag}"
        )

def validate_triadic_identity(identity: TriadicIdentity):
    """
    Ensures all three components of the triad are present.
    """
    if not identity.silence or not identity.noise or not identity.resonance:
        return False, "[Triadic Identity Failed: Incomplete Triad]"
    return True, "[Triadic Identity Satisfied]"

def tag_triadic_regime(identity: TriadicIdentity, regime: str):
    """
    Adds regime tags to triadic identity.
    regime: 'form' or 'non-form'
    """
    regime_tag = "[1/3 In-Formation]" if regime == "form" else "[2/3 Information]"
    return f"{identity.tags()} {regime_tag}"

def triadic_identity_decision(identity: TriadicIdentity):
    """
    Implements the triadic-identity portion of the v1.2 decision procedure.
    """
    ok, tag = validate_triadic_identity(identity)
    if not ok:
        return f"{tag} — please specify complete Silence, Noise, and Resonance."
 
    return f"{identity.tags()} [Triadic Identity Mapping Complete]"

def detect_triadic_drift(text: str):
    """
    Detects misuse of triadic identity as motif or branding.
    """
    drift_terms = [
        "triadic-themed",
        "triad-like branding",
        "triadic aesthetic",
        "triadic vibe"
    ]
    if any(term in text.lower() for term in drift_terms):
        return False, "[Self-Correction: Triadic Identity Drift Detected]"
    return True, "[Triadic Identity Stable]"

def correct_triadic_identity(text: str):
    """
    Applies triadic-identity drift detection and returns corrected output.
    """
    ok, tag = detect_triadic_drift(text)
    if ok:
        return f"{text} {tag}"
    return f"[Self-Correction: Triadic Identity Drift Detected] Correcting. {tag}"

def triadic_full(identity: TriadicIdentity, dimensional: dict):
    """
    Combines triadic identity, coherence, and lineage into a single tagged output.
    """
    # Coherence (conceptual import from Appendix G)
    def coherence_layer(triad: dict, dimensional: dict):
        if not all(k in triad and triad[k] for k in ("silence", "noise", "resonance")):
            return False, "[Coherence Layer Failed: Incomplete Triad]"
        if "name" not in dimensional or not dimensional["name"]:
            return False, "[Coherence Layer Failed: Dimensional Missing]"
        return True, "[Coherence Layer Satisfied]"
 
    triad_dict = {
        "silence": identity.silence,
        "noise": identity.noise,
        "resonance": identity.resonance
    }
 
    ok_coherence, coherence_tag = coherence_layer(triad_dict, dimensional)
    return f"{identity.tags()} [Dimensional: {dimensional.get('name', '')}] {coherence_tag}"

from dataclasses import dataclass
 
@dataclass
class HarmonicDimensional:
    name: str
    parent: str | None = None
    layer: int | None = None  # optional harmonic layer index
 
    def path(self):
        if self.parent:
            return f"{self.parent} → {self.name}"
        return self.name
 
    def tags(self):
        layer_tag = f"[Layer: {self.layer}]" if self.layer is not None else "[Layer: Unspecified]"
        return f"[Dimensional: {self.name}] [Parent: {self.parent or 'None'}] {layer_tag}"

def validate_harmonic_nesting(dimensionals: list[HarmonicDimensional]):
    """
    Ensures harmonic dimensionals form a coherent nested structure.
    """
    names = {d.name for d in dimensionals}
    for d in dimensionals:
        if d.parent and d.parent not in names:
            return False, f"[Coherence Failed: Parent Missing for {d.name}]"
    return True, "[Harmonic Nesting Satisfied]"

def build_harmonic_path(d: HarmonicDimensional, all_dims: dict[str, HarmonicDimensional]):
    """
    Builds full harmonic path from root to this dimensional.
    """
    path = [d.name]
    current = d
    while current.parent:
        parent = all_dims.get(current.parent)
        if not parent:
            break
        path.insert(0, parent.name)
        current = parent
    return " → ".join(path)

def harmonic_decision(d: HarmonicDimensional | None):
    """
    Implements the harmonic-dimensional portion of the v1.2 decision procedure.
    """
    if d is None or not d.name:
        return "[Uncertain — Harmonic Dimensional Context Missing]"
 
    return f"{d.tags()} [Harmonic Mapping Complete]"

def harmonic_coherence(triad: dict, dimensional: HarmonicDimensional):
    """
    Checks coherence between a triad and a harmonic dimensional.
    """
    if not all(k in triad and triad[k] for k in ("silence", "noise", "resonance")):
        return False, "[Coherence Layer Failed: Incomplete Triad]"
    if not dimensional.name:
        return False, "[Coherence Layer Failed: Dimensional Missing]"
    return True, "[Coherence Layer Satisfied]"

def detect_harmonic_drift(text: str):
    """
    Detects misuse of harmonic dimensionals as aesthetic or vague metaphor.
    """
    drift_terms = [
        "harmonic vibe",
        "harmonic aesthetic",
        "dimension-ish",
        "layer-ish"
    ]
    if any(term in text.lower() for term in drift_terms):
        return False, "[Self-Correction: Harmonic Drift Detected]"
    return True, "[Harmonic Context Stable]"

def correct_harmonic(text: str):
    """
    Applies harmonic drift detection and returns corrected output.
    """
    ok, tag = detect_harmonic_drift(text)
    if ok:
        return f"{text} {tag}"
    return f"[Self-Correction: Harmonic Drift Detected] Correcting. {tag}"

def tag_harmonic_full(concept: str, regime: str, module: str | None, dimensional: HarmonicDimensional):
    """
    Combines harmonic dimensional, regime, and lineage into a single tagged output.
    """
    regime_tag = "[1/3 In-Formation]" if regime == "form" else "[2/3 Information]"
    lineage_tag = f"[Lineage: {module}]" if module else "[Uncertain — Requesting Clarification]"
    return f"{concept} {regime_tag} {lineage_tag} {dimensional.tags()}"

from dataclasses import dataclass
from typing import Literal
 
RegimeTag = Literal["[1/3 In-Formation]", "[2/3 Information]"]
 
@dataclass
class Supsphere:
    name: str
    regime: RegimeTag
    continuity: str
    identity: str
    module: str | None = None
 
    def tags(self):
        lineage_tag = f"[Lineage: {self.module}]" if self.module else "[Uncertain — Requesting Clarification]"
        return (
            f"[Supsphere: {self.name}] "
            f"{self.regime} "
            f"[Continuity: {self.continuity}] "
            f"[Identity: {self.identity}] "
            f"{lineage_tag}"
        )

def validate_supsphere_continuity(s: Supsphere):
    """
    Ensures continuity and identity are present for a supsphere.
    """
    if not s.continuity or not s.identity:
        return False, "[Supsphere Continuity Failed: Missing Continuity or Identity]"
    return True, "[Supsphere Continuity Satisfied]"

def validate_supsphere_regime_pair(a: Supsphere, b: Supsphere):
    """
    Ensures two supspheres are not collapsed into a single regime.
    """
    if a.regime == b.regime and a.name != b.name:
        return False, "[Self-Correction: Supsphere Regime Collapse Detected]"
    return True, "[Supsphere Regime Separation Maintained]"

def tag_supsphere_harmonic(s: Supsphere, dimensional: dict):
    """
    Combines supsphere continuity with harmonic dimensional context.
    dimensional: {"name": ..., "parent": ...}
    """
    dim_tag = f"[Dimensional: {dimensional.get('name', '')}]"
    parent_tag = f"[Parent: {dimensional.get('parent', 'None')}]"
    return f"{s.tags()} {dim_tag} {parent_tag}"

def supsphere_decision(s: Supsphere | None):
    """
    Implements the supsphere portion of the v1.2 decision procedure.
    """
    if s is None:
        return "[Uncertain — Supsphere Context Missing]"
 
    ok, tag = validate_supsphere_continuity(s)
    if not ok:
        return f"{tag} — please specify continuity and identity."
 
    return f"{s.tags()} [Supsphere Mapping Complete]"

def detect_supsphere_drift(text: str):
    """
    Detects misuse of supspheres as vague metaphors or branding.
    """
    drift_terms = [
        "supsphere vibe",
        "supsphere aesthetic",
        "supsphere-themed",
        "supsphere-ish"
    ]
    if any(term in text.lower() for term in drift_terms):
        return False, "[Self-Correction: Supsphere Drift Detected]"
    return True, "[Supsphere Context Stable]"

def correct_supsphere(text: str):
    """
    Applies supsphere drift detection and returns corrected output.
    """
    ok, tag = detect_supsphere_drift(text)
    if ok:
        return f"{text} {tag}"
    return f"[Self-Correction: Supsphere Drift Detected] Correcting. {tag}"

def tag_supsphere_full(concept: str, s: Supsphere, triad: dict, dimensional: dict):
    """
    Combines supsphere continuity, regime, lineage, and coherence into a single tagged output.
    """
    # Minimal coherence check (inline)
    def coherence_layer(triad: dict, dimensional: dict):
        if not all(k in triad and triad[k] for k in ("silence", "noise", "resonance")):
            return False, "[Coherence Layer Failed: Incomplete Triad]"
        if "name" not in dimensional or not dimensional["name"]:
            return False, "[Coherence Layer Failed: Dimensional Missing]"
        return True, "[Coherence Layer Satisfied]"
 
    ok_coherence, coherence_tag = coherence_layer(triad, dimensional)
    dim_tag = f"[Dimensional: {dimensional.get('name', '')}]"
 
    return f"{concept} {s.tags()} {dim_tag} {coherence_tag}"

from dataclasses import dataclass
 
@dataclass
class ContinuityNode:
    name: str
    continuity: str
    module: str | None = None
 
    def tag(self):
        lineage_tag = f"[Lineage: {self.module}]" if self.module else "[Uncertain — Requesting Clarification]"
        return f"[Node: {self.name}] [Continuity: {self.continuity}] {lineage_tag}"

def propagate_continuity(a: ContinuityNode, b: ContinuityNode):
    """
    Propagates continuity from node A to node B if compatible.
    """
    if a.continuity != b.continuity:
        return False, "[Continuity Break Detected]"
    return True, f"[Continuity Propagated: {a.continuity}]"

def continuity_path(nodes: list[ContinuityNode]):
    """
    Builds a continuity path across multiple nodes.
    """
    tags = [n.tag() for n in nodes]
 
    # Check continuity consistency
    continuity_values = {n.continuity for n in nodes}
    if len(continuity_values) > 1:
        return False, "[Continuity Break Detected] " + " ".join(tags)
 
    return True, "[Continuity Path Stable] " + " → ".join(n.name for n in nodes)

def continuity_with_triad(node: ContinuityNode, triad: dict):
    """
    Integrates continuity with triadic structure.
    """
    if not all(k in triad and triad[k] for k in ("silence", "noise", "resonance")):
        return f"{node.tag()} [Coherence Layer Failed: Incomplete Triad]"
 
    return f"{node.tag()} [Triad: {triad['silence']}, {triad['noise']}, {triad['resonance']}]"

def continuity_with_dimensional(node: ContinuityNode, dimensional: dict):
    """
    Integrates continuity with harmonic dimensional context.
    """
    dim_tag = f"[Dimensional: {dimensional.get('name', '')}]"
    parent_tag = f"[Parent: {dimensional.get('parent', 'None')}]"
    return f"{node.tag()} {dim_tag} {parent_tag}"

def detect_continuity_drift(text: str):
    """
    Detects misuse of continuity as vague metaphor or aesthetic.
    """
    drift_terms = [
        "continuity vibe",
        "continuity aesthetic",
        "continuity-ish",
        "flowy continuity"
    ]
    if any(term in text.lower() for term in drift_terms):
        return False, "[Self-Correction: Continuity Drift Detected]"
    return True, "[Continuity Context Stable]"

def correct_continuity(text: str):
    """
    Applies continuity drift detection and returns corrected output.
    """
    ok, tag = detect_continuity_drift(text)
    if ok:
        return f"{text} {tag}"
    return f"[Self-Correction: Continuity Drift Detected] Correcting. {tag}"

def continuity_decision(node: ContinuityNode | None):
    """
    Implements the continuity portion of the v1.2 decision procedure.
    """
    if node is None:
        return "[Uncertain — Continuity Context Missing]"
 
    if not node.continuity:
        return "[Continuity Missing] — please specify continuity."
 
    return f"{node.tag()} [Continuity Mapping Complete]"

def tag_continuity_full(concept: str, node: ContinuityNode, regime: str, triad: dict, dimensional: dict):
    """
    Combines continuity, regime, lineage, and coherence into a single tagged output.
    """
    # Regime mapping
    regime_tag = "[1/3 In-Formation]" if regime == "form" else "[2/3 Information]"
 
    # Minimal coherence check
    def coherence_layer(triad: dict, dimensional: dict):
        if not all(k in triad and triad[k] for k in ("silence", "noise", "resonance")):
            return False, "[Coherence Layer Failed: Incomplete Triad]"
        if "name" not in dimensional or not dimensional["name"]:
            return False, "[Coherence Layer Failed: Dimensional Missing]"
        return True, "[Coherence Layer Satisfied]"
 
    ok_coherence, coherence_tag = coherence_layer(triad, dimensional)
    dim_tag = f"[Dimensional: {dimensional.get('name', '')}]"
 
    return f"{concept} {node.tag()} {regime_tag} {dim_tag} {coherence_tag}"

from dataclasses import dataclass
 
@dataclass
class IdentityNode:
    name: str
    identity: str
    module: str | None = None
 
    def tag(self):
        lineage_tag = f"[Lineage: {self.module}]" if self.module else "[Uncertain — Requesting Clarification]"
        return f"[Identity Node: {self.name}] [Identity: {self.identity}] {lineage_tag}"

def validate_identity_stability(nodes: list[IdentityNode]):
    """
    Ensures identity remains stable across a set of nodes.
    """
    identities = {n.identity for n in nodes}
    if len(identities) > 1:
        return False, "[Identity Fragmentation Detected]"
    return True, "[Identity Stable]"

def identity_path(nodes: list[IdentityNode]):
    """
    Builds an identity path across multiple nodes.
    """
    ok, tag = validate_identity_stability(nodes)
    path = " → ".join(n.name for n in nodes)
    return ok, f"{tag} [Identity Path: {path}]"

def identity_with_continuity(identity_node: IdentityNode, continuity: str):
    """
    Integrates identity with continuity description.
    """
    return f"{identity_node.tag()} [Continuity: {continuity}]"

def detect_identity_drift(text: str):
    """
    Detects misuse of identity as branding, aesthetic, or vague metaphor.
    """
    drift_terms = [
        "identity vibe",
        "identity aesthetic",
        "identity-themed",
        "identity-ish"
    ]
    if any(term in text.lower() for term in drift_terms):
        return False, "[Self-Correction: Identity Drift Detected]"
    return True, "[Identity Context Stable]"

def correct_identity(text: str):
    """
    Applies identity drift detection and returns corrected output.
    """
    ok, tag = detect_identity_drift(text)
    if ok:
        return f"{text} {tag}"
    return f"[Self-Correction: Identity Drift Detected] Correcting. {tag}"

def identity_decision(node: IdentityNode | None):
    """
    Implements the identity portion of the v1.2 decision procedure.
    """
    if node is None:
        return "[Uncertain — Identity Context Missing]"
 
    if not node.identity:
        return "[Identity Missing] — please specify identity."
 
    return f"{node.tag()} [Identity Mapping Complete]"

def tag_identity_full(concept: str, node: IdentityNode, regime: str, continuity: str, triad: dict, dimensional: dict):
    """
    Combines identity, regime, continuity, and coherence into a single tagged output.
    """
    regime_tag = "[1/3 In-Formation]" if regime == "form" else "[2/3 Information]"
 
    def coherence_layer(triad: dict, dimensional: dict):
        if not all(k in triad and triad[k] for k in ("silence", "noise", "resonance")):
            return False, "[Coherence Layer Failed: Incomplete Triad]"
        if "name" not in dimensional or not dimensional["name"]:
            return False, "[Coherence Layer Failed: Dimensional Missing]"
        return True, "[Coherence Layer Satisfied]"
 
    ok_coherence, coherence_tag = coherence_layer(triad, dimensional)
    dim_tag = f"[Dimensional: {dimensional.get('name', '')}]"
    continuity_tag = f"[Continuity: {continuity}]"
 
    return f"{concept} {node.tag()} {regime_tag} {continuity_tag} {dim_tag} {coherence_tag}"

from dataclasses import dataclass
 
@dataclass
class SupsphereNode:
    name: str
    regime: str
    continuity: str
    identity: str
    module: str | None = None
 
    def tag(self):
        lineage_tag = f"[Lineage: {self.module}]" if self.module else "[Uncertain — Requesting Clarification]"
        return (
            f"[Supsphere: {self.name}] "
            f"{self.regime} "
            f"[Continuity: {self.continuity}] "
            f"[Identity: {self.identity}] "
            f"{lineage_tag}"
        )

class SupsphereGraph:
    def __init__(self):
        self.nodes = {}
        self.edges = []  # (nodeA, nodeB, edge_type)
 
    def add_node(self, node: SupsphereNode):
        self.nodes[node.name] = node
 
    def add_edge(self, a: str, b: str, edge_type: str):
        self.edges.append((a, b, edge_type))

def continuity_edge(a: SupsphereNode, b: SupsphereNode):
    return (a.name, b.name, f"[Continuity Edge: {a.continuity}]")
 
def identity_edge(a: SupsphereNode, b: SupsphereNode):
    return (a.name, b.name, f"[Identity Edge: {a.identity}]")
 
def dimensional_edge(a: SupsphereNode, b: SupsphereNode, dimensional: str):
    return (a.name, b.name, f"[Dimensional Edge: {dimensional}]")

def detect_supsphere_regime_collapse(graph: SupsphereGraph):
    """
    Detects regime collapse across supsphere graph.
    """
    for a, b, _ in graph.edges:
        nodeA = graph.nodes[a]
        nodeB = graph.nodes[b]
        if nodeA.regime == nodeB.regime and nodeA.name != nodeB.name:
            return False, "[Self-Correction: Supsphere Regime Collapse Detected]"
    return True, "[Supsphere Regime Separation Maintained]"

def trace_supsphere_path(graph: SupsphereGraph, start: str, end: str):
    """
    Simple DFS path trace between two supspheres.
    """
    visited = set()
    stack = [(start, [start])]
 
    while stack:
        node, path = stack.pop()
        if node == end:
            return True, f"[Supsphere Path: {' → '.join(path)}]"
 
        visited.add(node)
        for a, b, _ in graph.edges:
            if a == node and b not in visited:
                stack.append((b, path + [b]))
 
    return False, "[No Supsphere Path Found]"

def validate_supsphere_graph(graph: SupsphereGraph):
    """
    Validates graph-level coherence: continuity, identity, and regime separation.
    """
    # Regime separation
    ok_regime, regime_tag = detect_supsphere_regime_collapse(graph)
 
    # Continuity consistency
    continuity_values = {n.continuity for n in graph.nodes.values()}
    ok_continuity = len(continuity_values) == 1
    continuity_tag = "[Continuity Stable]" if ok_continuity else "[Continuity Break Detected]"
 
    # Identity consistency
    identity_values = {n.identity for n in graph.nodes.values()}
    ok_identity = len(identity_values) == 1
    identity_tag = "[Identity Stable]" if ok_identity else "[Identity Fragmentation Detected]"
 
    return ok_regime and ok_continuity and ok_identity, f"{regime_tag} {continuity_tag} {identity_tag}"

def detect_supsphere_graph_drift(text: str):
    """
    Detects motif-level misuse of supsphere graphs.
    """
    drift_terms = [
        "supsphere web",
        "supsphere aesthetic graph",
        "graph-ish supsphere",
        "supsphere vibe network"
    ]
    if any(term in text.lower() for term in drift_terms):
        return False, "[Self-Correction: Supsphere Graph Drift Detected]"
    return True, "[Supsphere Graph Stable]"

def supsphere_graph_decision(graph: SupsphereGraph):
    """
    Implements the supsphere-graph portion of the v1.2 decision procedure.
    """
    ok, tag = validate_supsphere_graph(graph)
    if not ok:
        return f"{tag} — please specify missing continuity, identity, or regime separation."
    return f"{tag} [Supsphere Graph Mapping Complete]"

def tag_supsphere_graph_full(graph: SupsphereGraph, triad: dict, dimensional: dict):
    """
    Combines graph-level supsphere structure with regime, lineage, and coherence.
    """
    # Minimal coherence check
    def coherence_layer(triad: dict, dimensional: dict):
        if not all(k in triad and triad[k] for k in ("silence", "noise", "resonance")):
            return False, "[Coherence Layer Failed: Incomplete Triad]"
        if "name" not in dimensional or not dimensional["name"]:
            return False, "[Coherence Layer Failed: Dimensional Missing]"
        return True, "[Coherence Layer Satisfied]"
 
    ok_coherence, coherence_tag = coherence_layer(triad, dimensional)
    dim_tag = f"[Dimensional: {dimensional.get('name', '')}]"
 
    ok_graph, graph_tag = validate_supsphere_graph(graph)
 
    return f"{graph_tag} {dim_tag} {coherence_tag}"

from dataclasses import dataclass
 
@dataclass
class ContinuityDiagnostic:
    ok: bool
    message: str
 
    def tag(self):
        status = "[Continuity OK]" if self.ok else "[Continuity Issue]"
        return f"{status} {self.message}"

def diagnose_node_continuity(node_name: str, continuity: str | None):
    """
    Diagnoses continuity for a single node.
    """
    if not continuity:
        return ContinuityDiagnostic(False, f"[Node: {node_name}] Continuity missing.")
    return ContinuityDiagnostic(True, f"[Node: {node_name}] Continuity present: {continuity}.")

def diagnose_multi_continuity(nodes: dict[str, str]):
    """
    Diagnoses continuity consistency across multiple nodes.
    nodes: {name: continuity}
    """
    values = set(nodes.values())
    if len(values) <= 1:
        return ContinuityDiagnostic(True, "[Continuity Stable Across Nodes]")
    return ContinuityDiagnostic(False, f"[Continuity Break Detected] Values: {', '.join(values)}")

def diagnose_continuity_loop(path: list[str]):
    """
    Detects simple continuity loops in a path.
    """
    if len(path) != len(set(path)):
        return ContinuityDiagnostic(False, f"[Continuity Loop Detected] Path: {' → '.join(path)}")
    return ContinuityDiagnostic(True, f"[No Continuity Loop] Path: {' → '.join(path)}")

def diagnose_continuity_ambiguity(continuity: str):
    """
    Flags overly vague or metaphorical continuity descriptions.
    """
    vague_terms = ["vibe", "aesthetic", "flowy", "kind of", "sort of"]
    if any(t in continuity.lower() for t in vague_terms):
        return ContinuityDiagnostic(False, f"[Continuity Ambiguous] {continuity}")
    return ContinuityDiagnostic(True, f"[Continuity Specific] {continuity}")

def diagnose_continuity_regime(continuity: str, regime: str):
    """
    Ensures continuity is being applied in the correct regime context.
    """
    if regime not in ("form", "non-form"):
        return ContinuityDiagnostic(False, "[Regime Unknown] Cannot assess continuity.")
 
    if regime == "form":
        msg = "[Form-Regime Continuity] Bound to physical encoding or propagation."
    else:
        msg = "[Non-Form Continuity] Bound to meaning, identity, or invariant structure."
 
    return ContinuityDiagnostic(True, msg + f" Continuity: {continuity}")

def diagnose_continuity_coherence(continuity: str, triad: dict, dimensional: dict):
    """
    Diagnoses continuity in relation to triad and dimensional coherence.
    """
    triad_ok = all(k in triad and triad[k] for k in ("silence", "noise", "resonance"))
    dim_ok = "name" in dimensional and dimensional["name"]
 
    if not triad_ok or not dim_ok:
        return ContinuityDiagnostic(
            False,
            "[Coherence Layer Failed] Continuity cannot be trusted without complete triad and dimensional."
        )
 
    return ContinuityDiagnostic(
        True,
        f"[Coherence Layer Satisfied] Continuity: {continuity} Triad: {triad} Dimensional: {dimensional['name']}"
    )

def run_continuity_diagnostics(node_name: str, continuity: str | None, regime: str, triad: dict, dimensional: dict):
    """
    Runs a basic continuity diagnostic suite and returns tagged messages.
    """
    results = []
 
    results.append(diagnose_node_continuity(node_name, continuity))
    if continuity:
        results.append(diagnose_continuity_ambiguity(continuity))
        results.append(diagnose_continuity_regime(continuity, regime))
        results.append(diagnose_continuity_coherence(continuity, triad, dimensional))
 
    return [r.tag() for r in results]

from dataclasses import dataclass
 
@dataclass
class SupsphereRegion:
    name: str
    regime: str
    continuity: str
    identity: str
    module: str | None = None
 
    def tag(self):
        lineage_tag = f"[Lineage: {self.module}]" if self.module else "[Uncertain — Requesting Clarification]"
        return (
            f"[Supsphere Region: {self.name}] "
            f"{self.regime} "
            f"[Continuity: {self.continuity}] "
            f"[Identity: {self.identity}] "
            f"{lineage_tag}"
        )

@dataclass
class TopologyRelation:
    a: str
    b: str
    relation: str  # "adjacent", "overlap", "disjoint"
 
    def tag(self):
        return f"[Topology: {self.a} {self.relation} {self.b}]"

class SupsphereTopology:
    def __init__(self):
        self.regions: dict[str, SupsphereRegion] = {}
        self.relations: list[TopologyRelation] = []
 
    def add_region(self, region: SupsphereRegion):
        self.regions[region.name] = region
 
    def add_relation(self, a: str, b: str, relation: str):
        self.relations.append(TopologyRelation(a, b, relation))

def diagnose_regime_overlap(topology: SupsphereTopology):
    """
    Detects problematic overlaps between supspheres in the same regime.
    """
    for rel in topology.relations:
        if rel.relation == "overlap":
            ra = topology.regions[rel.a]
            rb = topology.regions[rel.b]
            if ra.regime == rb.regime and ra.name != rb.name:
                return False, "[Self-Correction: Supsphere Regime Overlap Detected]"
    return True, "[Supsphere Regime Topology Stable]"

def diagnose_continuity_boundaries(topology: SupsphereTopology):
    """
    Checks continuity consistency across adjacent regions.
    """
    for rel in topology.relations:
        if rel.relation == "adjacent":
            ra = topology.regions[rel.a]
            rb = topology.regions[rel.b]
            if ra.continuity != rb.continuity:
                return False, "[Continuity Boundary Break Detected]"
    return True, "[Continuity Boundaries Stable]"

def diagnose_identity_topology(topology: SupsphereTopology):
    """
    Checks identity stability across overlapping regions.
    """
    for rel in topology.relations:
        if rel.relation == "overlap":
            ra = topology.regions[rel.a]
            rb = topology.regions[rel.b]
            if ra.identity != rb.identity:
                return False, "[Identity Fragmentation Across Overlap Detected]"
    return True, "[Identity Topology Stable]"

def detect_supsphere_topology_drift(text: str):
    """
    Detects motif-level misuse of topology (aesthetic, vague metaphor).
    """
    drift_terms = [
        "topology vibe",
        "topology aesthetic",
        "topology-ish",
        "supsphere cloud"
    ]
    if any(t in text.lower() for t in drift_terms):
        return False, "[Self-Correction: Supsphere Topology Drift Detected]"
    return True, "[Supsphere Topology Context Stable]"

def supsphere_topology_decision(topology: SupsphereTopology):
    """
    Implements the supsphere-topology portion of the v1.2 decision procedure.
    """
    ok_regime, regime_tag = diagnose_regime_overlap(topology)
    ok_continuity, continuity_tag = diagnose_continuity_boundaries(topology)
    ok_identity, identity_tag = diagnose_identity_topology(topology)
 
    all_ok = ok_regime and ok_continuity and ok_identity
    if not all_ok:
        return f"{regime_tag} {continuity_tag} {identity_tag} — please resolve topological conflicts."
 
    return f"{regime_tag} {continuity_tag} {identity_tag} [Supsphere Topology Mapping Complete]"

def tag_supsphere_topology_full(topology: SupsphereTopology, triad: dict, dimensional: dict):
    """
    Combines topology diagnostics with coherence-layer tags.
    """
    def coherence_layer(triad: dict, dimensional: dict):
        if not all(k in triad and triad[k] for k in ("silence", "noise", "resonance")):
            return False, "[Coherence Layer Failed: Incomplete Triad]"
        if "name" not in dimensional or not dimensional["name"]:
            return False, "[Coherence Layer Failed: Dimensional Missing]"
        return True, "[Coherence Layer Satisfied]"
 
    ok_topology, topo_tag = diagnose_regime_overlap(topology)
    ok_continuity, cont_tag = diagnose_continuity_boundaries(topology)
    ok_identity, id_tag = diagnose_identity_topology(topology)
 
    ok_coherence, coherence_tag = coherence_layer(triad, dimensional)
    dim_tag = f"[Dimensional: {dimensional.get('name', '')}]"
 
    return f"{topo_tag} {cont_tag} {id_tag} {dim_tag} {coherence_tag}"

from dataclasses import dataclass
 
@dataclass
class TriadNode:
    name: str
    silence: str
    noise: str
    resonance: str
    module: str | None = None
 
    def tag(self):
        lineage_tag = f"[Lineage: {self.module}]" if self.module else "[Uncertain — Requesting Clarification]"
        return (
            f"[Triad: {self.name}] "
            f"[Silence: {self.silence}] "
            f"[Noise: {self.noise}] "
            f"[Resonance: {self.resonance}] "
            f"{lineage_tag}"
        )

class TriadicGraph:
    def __init__(self):
        self.nodes: dict[str, TriadNode] = {}
        self.edges: list[tuple[str, str, str]] = []  # (nodeA, nodeB, edge_type)
 
    def add_node(self, node: TriadNode):
        self.nodes[node.name] = node
 
    def add_edge(self, a: str, b: str, edge_type: str):
        self.edges.append((a, b, edge_type))

def harmonic_edge(a: TriadNode, b: TriadNode, dimensional: str):
    return (a.name, b.name, f"[Harmonic Edge: {dimensional}]")
 
def continuity_edge(a: TriadNode, b: TriadNode, continuity: str):
    return (a.name, b.name, f"[Continuity Edge: {continuity}]")
 
def identity_edge(a: TriadNode, b: TriadNode, identity: str):
    return (a.name, b.name, f"[Identity Edge: {identity}]")