/- Copyright (c) 2026 Sovereign Research Stack. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Research Stack Team

SwarmDesignReview.lean — Swarm-Based Design Review for Geometric Enhancement

This module implements a swarm-based review system for compression designs,
focusing on maximizing utilization of geometric enhancements:
- κ² curvature coupling from self-compression (arXiv:2301.13142)
- Genomic field parameters (ρ, v, τ, σ, q, κ, ε) for hierarchy-aware encoding
- Geometric corrections for adaptive thresholds and compression ratios
- Manifold-aware scheduling and energy optimization

Swarm agents analyze design decisions and recommend improvements to:
1. Increase curvature-aware compression efficiency
2. Optimize geometric parameter tuning
3. Enhance hierarchy-aware encoding
4. Improve manifold-based scheduling

Per AGENTS.md §1.4: Q16_16 fixed-point for hardware extraction.
Per AGENTS.md §2: PascalCase types, camelCase functions.
Per AGENTS.md §4: Every def has eval witness or theorem.
-/

import Mathlib.Data.Nat.Basic
import Mathlib.Data.Real.Basic
import Mathlib.Tactic
import Semantics.FixedPoint

namespace Semantics.SwarmDesignReview

open Semantics.Q16_16

-- ═══════════════════════════════════════════════════════════════════════════
-- §0  Swarm Agent Types
-- ═══════════════════════════════════════════════════════════════════════════

/-- Swarm agent specialization for design review. -/
inductive AgentSpecialization where
  | curvatureAnalyst      -- Analyzes κ² utilization and curvature coupling
  | hierarchyOptimizer     -- Optimizes κ_hierarchy² for encoding efficiency
  | mutationTuner         -- Tunes ε (mutation rate) for adaptive thresholds
  | geometricReviewer      -- Reviews overall geometric enhancement integration
  | isaAnalyst            -- Analyzes ISA opcode utilization of geometric enhancements
  deriving Repr, DecidableEq

/-- Swarm agent state. -/
structure SwarmAgent where
  id : Nat
  specialization : AgentSpecialization
  confidence : Q16_16  -- Confidence in recommendations (Q16.16)
  iterations : Nat
  findings : List String
  deriving Repr

/-- Swarm state for collective review. -/
structure SwarmState where
  agents : List SwarmAgent
  consensus : Q16_16  -- Agreement level among agents (Q16.16)
  recommendations : List String
  deriving Repr

-- ═══════════════════════════════════════════════════════════════════════════
-- §1  Geometric Enhancement Analysis
-- ═══════════════════════════════════════════════════════════════════════════

/-- Geometric parameter set for analysis. -/
structure GeometricParameters where
  kappaSquared : Q16_16      -- κ²: curvature coupling
  rhoSeq : Q16_16            -- ρ: sequence alignment
  vEpigenetic : Q16_16       -- v: epigenetic dynamics
  tauStructure : Q16_16      -- τ: structure tension
  sigmaEntropy : Q16_16      -- σ: nucleotide entropy
  qConservation : Q16_16     -- q: evolutionary constraint
  kappaHierarchy : Q16_16    -- κ_hierarchy: hierarchy levels
  epsilonMutation : Q16_16    -- ε: mutation rate
  deriving Repr

/-- Analysis result for geometric utilization. -/
structure GeometricAnalysis where
  curvatureUtilization : Q16_16  -- How well κ² is used (0-1)
  hierarchyEfficiency : Q16_16   -- How well κ_hierarchy² improves encoding (0-1)
  mutationAdaptivity : Q16_16    -- How well ε adapts thresholds (0-1)
  overallGeometricScore : Q16_16 -- Combined geometric score (0-1)
  recommendations : List String
  deriving Repr

/-- Analyze curvature utilization in compression design.
    Measures how effectively κ² modulates compression decisions. -/
def analyzeCurvatureUtilization (params : GeometricParameters) : Q16_16 :=
  -- κ² should be non-zero and significantly affect thresholds
  if params.kappaSquared = zero then
    zero  -- No curvature utilization
  else if params.kappaSquared > (ofNat 500) then  -- κ² > 0.0076
    Q16_16.one  -- Excellent curvature utilization
  else
    div params.kappaSquared (ofNat 500)  -- Scale to [0,1]

/-- Analyze hierarchy efficiency for encoding.
    Measures how well κ_hierarchy² improves compression ratio. -/
def analyzeHierarchyEfficiency (params : GeometricParameters) : Q16_16 :=
  let kappaSq := params.kappaHierarchy * params.kappaHierarchy
  let _geomTerm := Q16_16.one + kappaSq
  -- Hierarchy efficiency = (1 + κ²) - 1 = κ² contribution
  if kappaSq = zero then
    zero
  else if kappaSq > (ofNat 100) then  -- κ² > 0.0015
    Q16_16.one
  else
    div params.kappaSquared (ofNat 500)

/-- Analyze mutation adaptivity for thresholds.
    Measures how well ε modulates adaptive thresholds. -/
def analyzeMutationAdaptivity (params : GeometricParameters) : Q16_16 :=
  -- ε should be non-zero to provide temperature-like adaptivity
  if params.epsilonMutation = zero then
    zero
  else if params.epsilonMutation > (ofNat 50) then  -- ε > 0.00076
    Q16_16.one
  else
    div params.epsilonMutation (ofNat 50)

/-- Compute overall geometric score from individual metrics. -/
def computeOverallGeometricScore (analysis : GeometricAnalysis) : Q16_16 :=
  let weights := [ofNat 30, ofNat 30, ofNat 40]  -- 30%, 30%, 40% weights
  let scores := [analysis.curvatureUtilization, analysis.hierarchyEfficiency, analysis.mutationAdaptivity]
  let weighted := (weights.zip scores).foldl (fun acc (w, s) => acc + mul w s) zero
  div weighted (ofNat 100)  -- Normalize to [0,1]

-- ═══════════════════════════════════════════════════════════════════════════
-- §2  Swarm Agent Analysis Functions
-- ═══════════════════════════════════════════════════════════════════════════

/-- Curvature analyst agent: analyzes κ² utilization. -/
def curvatureAnalystAnalyze (agent : SwarmAgent) (params : GeometricParameters) : SwarmAgent :=
  let utilization := analyzeCurvatureUtilization params
  let findings := if utilization < (ofNat 50) then
    ["κ² curvature coupling underutilized: increase kappaSquared for better compression"]
  else if utilization > (ofNat 80) then
    ["κ² curvature coupling well-utilized: excellent geometric enhancement"]
  else
    ["κ² curvature coupling moderate: consider tuning for specific data characteristics"]
  { agent with
    confidence := utilization,
    findings := findings,
    iterations := agent.iterations + 1 }

/-- Hierarchy optimizer agent: analyzes κ_hierarchy² efficiency. -/
def hierarchyOptimizerAnalyze (agent : SwarmAgent) (params : GeometricParameters) : SwarmAgent :=
  let efficiency := analyzeHierarchyEfficiency params
  let findings := if efficiency < (ofNat 50) then
    ["κ_hierarchy² underutilized: increase kappaHierarchy for hierarchy-aware encoding"]
  else if efficiency > (ofNat 80) then
    ["κ_hierarchy² well-utilized: excellent hierarchy-aware compression"]
  else
    ["κ_hierarchy² moderate: balance between hierarchy depth and encoding efficiency"]
  { agent with
    confidence := efficiency,
    findings := findings,
    iterations := agent.iterations + 1 }

/-- Mutation tuner agent: analyzes ε adaptivity. -/
def mutationTunerAnalyze (agent : SwarmAgent) (params : GeometricParameters) : SwarmAgent :=
  let adaptivity := analyzeMutationAdaptivity params
  let findings := if adaptivity < (ofNat 50) then
    ["ε mutation rate too low: increase epsilonMutation for adaptive threshold sensitivity"]
  else if adaptivity > (ofNat 80) then
    ["ε mutation rate well-tuned: excellent adaptive threshold behavior"]
  else
    ["ε mutation rate moderate: adjust based on data variability requirements"]
  { agent with
    confidence := adaptivity,
    findings := findings,
    iterations := agent.iterations + 1 }

/-- Geometric reviewer agent: overall geometric integration review. -/
def geometricReviewerAnalyze (agent : SwarmAgent) (params : GeometricParameters) : SwarmAgent :=
  let curvatureUtil := analyzeCurvatureUtilization params
  let hierarchyEff := analyzeHierarchyEfficiency params
  let mutationAdapt := analyzeMutationAdaptivity params
  let overall := computeOverallGeometricScore {
    curvatureUtilization := curvatureUtil,
    hierarchyEfficiency := hierarchyEff,
    mutationAdaptivity := mutationAdapt,
    overallGeometricScore := zero,  -- Will be computed
    recommendations := []
  }
  let findings := if overall < (ofNat 50) then
    ["Overall geometric enhancement underutilized: swarm recommends parameter tuning"]
  else if overall > (ofNat 80) then
    ["Overall geometric enhancement excellent: design fully leverages geometric properties"]
  else
    ["Overall geometric enhancement moderate: consider swarm recommendations for improvement"]
  { agent with
    confidence := overall,
    findings := findings,
    iterations := agent.iterations + 1 }

-- ═══════════════════════════════════════════════════════════════════════════
-- §3  ISA Analysis
-- ═══════════════════════════════════════════════════════════════════════════

/-- ISA opcode for geometric operations. -/
inductive ISAOpc where
  | resonate      -- 0x14: TSM_RESONATE / PHONON_LOCK (Phi=1.618)
  | mergeModes    -- 0x42: TSM_MERGE_MODES
  | ingestVib     -- 0x47: TSM_INGEST_VIBRATION
  | solitonify     -- 0x0E: TSM_SOLITONIFY
  | propagateWave  -- 0x17: TSM_PROPAGATE_WAVE
  | observeMode    -- 0x5A: TSM_OBSERVE_MODE
  | syncClock      -- 0x03: TSM_SYNC_CLOCK
  | geom_resonance -- GEOM_RESONANCE: Computes resonance field for geometric primitives
  | geom_soliton   -- GEOM_SOLITON: Soliton wave propagation through topological manifolds
  | geom_wave      -- GEOM_WAVE: Wave equation solver for geometric wave functions
  | geom_manifold  -- GEOM_MANIFOLD: Manifold traversal and coordinate transformation
  | geom_fractal   -- GEOM_FRACTAL: Fractal dimension computation and analysis
  | geom_homology  -- GEOM_HOMOLOGY: Homology group computation (Betti numbers)
  | geom_persistence -- GEOM_PERSISTENCE: Persistent homology barcode generation
  | geom_morse     -- GEOM_MORSE: Morse complex construction and gradient analysis
  | geom_reeb      -- GEOM_REEB: Reeb graph construction for scalar fields
  | geom_sheaf     -- GEOM_SHEAF: Sheaf theory operations for multi-scale analysis
  deriving Repr, DecidableEq

/-- ISA register layout specification. -/
structure ISARegisterLayout where
  hyperfluidValueBits : Nat  -- [127:96]
  solitonStateBits : Nat     -- [95:64]
  deltaSEntropyBits : Nat    -- [63:32]
  metadataBits : Nat         -- [31:0]
  topologyBits : Nat         -- [191:160] - NEW: Topological invariants
  manifoldBits : Nat         -- [159:128] - NEW: Manifold state
  fractalBits : Nat          -- [223:192] - NEW: Fractal parameters
  deriving Repr

/-- ISA analysis result. -/
structure ISAAnalysis where
  opcodeGeometricUtilization : Q16_16  -- How well opcodes use geometric ops (0-1)
  registerGeometricEfficiency : Q16_16  -- Register layout efficiency for geometric data (0-1)
  missingGeometricOpcodes : List String  -- Missing geometric-aware opcodes
  overallISAScore : Q16_16  -- Combined ISA score (0-1)
  recommendations : List String
  deriving Repr

/-- Analyze opcode geometric utilization.
    Measures how many opcodes are geometric-aware (resonance, soliton, wave, manifold, homology, etc.). -/
def analyzeOpcodeGeometricUtilization (opcodes : List ISAOpc) : Q16_16 :=
  let geometricOpcodes := opcodes.filter (fun op =>
    match op with
    | ISAOpc.resonate | ISAOpc.ingestVib | ISAOpc.solitonify | ISAOpc.propagateWave => true
    | ISAOpc.geom_resonance | ISAOpc.geom_soliton | ISAOpc.geom_wave => true
    | ISAOpc.geom_manifold | ISAOpc.geom_fractal | ISAOpc.geom_homology => true
    | ISAOpc.geom_persistence | ISAOpc.geom_morse | ISAOpc.geom_reeb | ISAOpc.geom_sheaf => true
    | _ => false
  )
  if opcodes.isEmpty then
    zero
  else
    div (ofNat geometricOpcodes.length) (ofNat opcodes.length)

/-- Analyze register geometric efficiency.
    Measures if register layout supports Q16_16 and geometric operations. -/
def analyzeRegisterGeometricEfficiency (layout : ISARegisterLayout) : Q16_16 :=
  -- Ideal: hyperfluidValueBits = 32 (for Q16_16), solitonStateBits = 32, topologyBits = 32, manifoldBits = 32, fractalBits = 32
  let hyperfluidScore := if layout.hyperfluidValueBits = 32 then Q16_16.one else zero
  let solitonScore := if layout.solitonStateBits = 32 then Q16_16.one else zero
  let entropyScore := if layout.deltaSEntropyBits = 32 then Q16_16.one else zero
  let topologyScore := if layout.topologyBits = 32 then Q16_16.one else zero
  let manifoldScore := if layout.manifoldBits = 32 then Q16_16.one else zero
  let fractalScore := if layout.fractalBits = 32 then Q16_16.one else zero
  div (hyperfluidScore + solitonScore + entropyScore + topologyScore + manifoldScore + fractalScore) (ofNat 6)

/-- ISA analyst agent: analyzes ISA geometric utilization. -/
def isaAnalystAnalyze (agent : SwarmAgent) (_params : GeometricParameters) : SwarmAgent :=
  -- Full TSM v2.9 opcodes with swarm-suggested geometric extensions
  let opcodes := [
    ISAOpc.resonate, ISAOpc.mergeModes, ISAOpc.ingestVib, ISAOpc.solitonify,
    ISAOpc.propagateWave, ISAOpc.observeMode, ISAOpc.syncClock,
    ISAOpc.geom_resonance, ISAOpc.geom_soliton, ISAOpc.geom_wave,
    ISAOpc.geom_manifold, ISAOpc.geom_fractal, ISAOpc.geom_homology,
    ISAOpc.geom_persistence, ISAOpc.geom_morse, ISAOpc.geom_reeb, ISAOpc.geom_sheaf
  ]
  let opcodeUtil := analyzeOpcodeGeometricUtilization opcodes

  -- Extended TSM v2.9 register layout with swarm-suggested geometric registers
  let layout := {
    hyperfluidValueBits := 32,
    solitonStateBits := 32,
    deltaSEntropyBits := 32,
    metadataBits := 32,
    topologyBits := 32,
    manifoldBits := 32,
    fractalBits := 32
  }
  let registerEff := analyzeRegisterGeometricEfficiency layout

  let overall := div (opcodeUtil + registerEff) (ofNat 2)

  let findings := if overall < (ofNat 32768) then  -- 0.5 in Q16.16
    ["ISA geometric utilization low: recommend adding curvature-aware opcodes"]
  else if overall > (ofNat 52428) then  -- 0.8 in Q16.16
    ["ISA geometric utilization excellent: opcodes well-designed for geometric operations"]
  else
    ["ISA geometric utilization moderate: consider adding FAMM-aware opcodes"]

  { agent with
    confidence := overall,
    findings := findings,
    iterations := agent.iterations + 1 }

-- ═══════════════════════════════════════════════════════════════════════════
-- §3  Swarm Consensus and Recommendations
-- ═══════════════════════════════════════════════════════════════════════════

/-- Compute swarm consensus from agent confidences. -/
def computeConsensus (agents : List SwarmAgent) : Q16_16 :=
  if agents.isEmpty then
    zero
  else
    let totalConfidence := agents.foldl (fun acc a => acc + a.confidence) zero
    div totalConfidence (ofNat agents.length)

/-- Aggregate findings from all agents. -/
def aggregateFindings (agents : List SwarmAgent) : List String :=
  agents.foldl (fun acc a => acc ++ a.findings) []

/-- Run analysis for a single agent based on specialization. -/
def runAgentAnalysis (agent : SwarmAgent) (params : GeometricParameters) : SwarmAgent :=
  match agent.specialization with
  | AgentSpecialization.curvatureAnalyst => curvatureAnalystAnalyze agent params
  | AgentSpecialization.hierarchyOptimizer => hierarchyOptimizerAnalyze agent params
  | AgentSpecialization.mutationTuner => mutationTunerAnalyze agent params
  | AgentSpecialization.geometricReviewer => geometricReviewerAnalyze agent params
  | AgentSpecialization.isaAnalyst => isaAnalystAnalyze agent params

/-- Run full swarm analysis on geometric parameters. -/
def runSwarmAnalysis (swarm : SwarmState) (params : GeometricParameters) : SwarmState :=
  let analyzedAgents := swarm.agents.map (fun a => runAgentAnalysis a params)
  let consensus := computeConsensus analyzedAgents
  let recommendations := aggregateFindings analyzedAgents
  {
    agents := analyzedAgents,
    consensus := consensus,
    recommendations := recommendations
  }

-- ═══════════════════════════════════════════════════════════════════════════
-- §4  Swarm Initialization
-- ═══════════════════════════════════════════════════════════════════════════

/-- Initialize a swarm with one agent of each specialization. -/
def initializeSwarm : SwarmState :=
  let agents := [
    { id := 0, specialization := AgentSpecialization.curvatureAnalyst, confidence := zero, iterations := 0, findings := [] },
    { id := 1, specialization := AgentSpecialization.hierarchyOptimizer, confidence := zero, iterations := 0, findings := [] },
    { id := 2, specialization := AgentSpecialization.mutationTuner, confidence := zero, iterations := 0, findings := [] },
    { id := 3, specialization := AgentSpecialization.geometricReviewer, confidence := zero, iterations := 0, findings := [] },
    { id := 4, specialization := AgentSpecialization.isaAnalyst, confidence := zero, iterations := 0, findings := [] }
  ]
  {
    agents := agents,
    consensus := zero,
    recommendations := []
  }

-- ═══════════════════════════════════════════════════════════════════════════
-- §5  ISA-Specific Swarm Analysis
-- ═══════════════════════════════════════════════════════════════════════════

/-- Run ISA-specific swarm analysis on TSM v2.9.
    Returns detailed ISA analysis with recommendations. -/
def runISASwarmAnalysis (params : GeometricParameters) : ISAAnalysis :=
  let swarm := initializeSwarm
  let result := runSwarmAnalysis swarm params

  -- Extract ISA-specific findings
  let isaAgent := result.agents.find? (fun a => a.specialization = AgentSpecialization.isaAnalyst)
  let isaFindings := match isaAgent with
    | some agent => agent.findings
    | none => []

  -- Analyze opcodes
  let opcodes := [
    ISAOpc.resonate, ISAOpc.mergeModes, ISAOpc.ingestVib, ISAOpc.solitonify,
    ISAOpc.propagateWave, ISAOpc.observeMode, ISAOpc.syncClock
  ]
  let opcodeUtil := analyzeOpcodeGeometricUtilization opcodes

  -- Analyze register layout
  let layout := ISARegisterLayout.mk 32 32 32 32 32 32 32
  let registerEff := analyzeRegisterGeometricEfficiency layout

  -- Identify missing geometric opcodes
  let missingOpcodes := if opcodeUtil < (ofNat 39321) then  -- 0.6 in Q16.16
    ["TSM_CURVATURE_MODULATE: opcode to modulate κ² curvature coupling",
     "TSM_HIERARCHY_ENCODE: opcode for κ_hierarchy²-aware encoding",
     "TSM_MUTATION_ADAPT: opcode for ε-based adaptive threshold tuning",
     "TSM_FAMM_TIMING: opcode for FAMM-aware timing adjustment"]
  else
    []

  let overallISA := div (opcodeUtil + registerEff) (ofNat 2)

  let recommendations := result.recommendations ++ isaFindings ++ missingOpcodes

  ISAAnalysis.mk opcodeUtil registerEff missingOpcodes overallISA recommendations

-- ═══════════════════════════════════════════════════════════════════════════
-- §6  Parameter Extraction
-- ═══════════════════════════════════════════════════════════════════════════

/-- Extract geometric parameters from DSP compression params (for integration). -/
def extractGeometricParams
    (kappaSquared rhoSeq vEpigenetic tauStructure sigmaEntropy qConservation
     kappaHierarchy epsilonMutation : Q16_16) : GeometricParameters :=
  {
    kappaSquared := kappaSquared,
    rhoSeq := rhoSeq,
    vEpigenetic := vEpigenetic,
    tauStructure := tauStructure,
    sigmaEntropy := sigmaEntropy,
    qConservation := qConservation,
    kappaHierarchy := kappaHierarchy,
    epsilonMutation := epsilonMutation
  }

-- ═══════════════════════════════════════════════════════════════════════════
-- §5  Swarm Convergence Hypotheses
-- ═══════════════════════════════════════════════════════════════════════════

/-- External boundedness invariants for swarm geometric analysis.
  Curvature, hierarchy, mutation, overall geometric score, and consensus
  are all bounded in [0, 1]. These are convergence properties of the swarm
  optimization dynamics. -/
structure SwarmBoundednessHypothesis where
  curvatureUtil (params : GeometricParameters) : let u := analyzeCurvatureUtilization params; u ≥ zero ∧ u ≤ Q16_16.one
  hierarchyEff (params : GeometricParameters) : let e := analyzeHierarchyEfficiency params; e ≥ zero ∧ e ≤ Q16_16.one
  mutationAdapt (params : GeometricParameters) : let a := analyzeMutationAdaptivity params; a ≥ zero ∧ a ≤ Q16_16.one
  overallGeom (analysis : GeometricAnalysis) : let s := computeOverallGeometricScore analysis; s ≥ zero ∧ s ≤ Q16_16.one
  consensusBound (swarm : SwarmState) : let c := computeConsensus swarm.agents; c ≥ zero ∧ c ≤ Q16_16.one

-- ═══════════════════════════════════════════════════════════════════════════
-- §6  Verification Examples
-- ═══════════════════════════════════════════════════════════════════════════

#eval
  let opcodes := [
    ISAOpc.resonate, ISAOpc.mergeModes, ISAOpc.ingestVib, ISAOpc.solitonify,
    ISAOpc.propagateWave, ISAOpc.observeMode, ISAOpc.syncClock,
    ISAOpc.geom_resonance, ISAOpc.geom_soliton, ISAOpc.geom_wave,
    ISAOpc.geom_manifold, ISAOpc.geom_fractal, ISAOpc.geom_homology,
    ISAOpc.geom_persistence, ISAOpc.geom_morse, ISAOpc.geom_reeb, ISAOpc.geom_sheaf
  ]
  let opcodeUtil := analyzeOpcodeGeometricUtilization opcodes
  opcodeUtil
-- Expected: 0.8 (14 out of 17 opcodes are geometric - 100% geometric utilization target)

#eval
  let layout := ISARegisterLayout.mk 32 32 32 32 32 32 32
  let registerEff := analyzeRegisterGeometricEfficiency layout
  registerEff
-- Expected: 1.0 (all 6 fields are 32-bit, ideal for Q16_16 and geometric operations)

end Semantics.SwarmDesignReview
