Implement Hive runtime structural upgrades

.gitignore

@@ -7,3 +7,4 @@ DerivedData/
 .swiftpm/configuration/registries.json
 .swiftpm/xcode/package.xcworkspace/contents.xcworkspacedata
 .netrc
+.wax-repo/

AGENTS.md

@@ -4,4 +4,61 @@ Always
 1. Use swift 6.2 best practices
 
 Do NOT:
-1. Edit Plan Documents
+1. Edit Plan Documents
+
+---
+
+## WaxMCP Memory Protocol (Mandatory)
+
+Use the WaxMCP tools to persist and retrieve context across sessions. This prevents context loss during long-running tasks and enables continuity when resuming work.
+
+### Tool Reference
+
+| Tool | Purpose | Key Params |
+|------|---------|------------|
+| `wax_remember` | Store a memory | `content` (text), `metadata` (dict) |
+| `wax_recall` | Retrieve memories by semantic query | `query` (text), `limit` (int) |
+| `wax_search` | Raw search hits (text or hybrid) | `query` (text) |
+| `wax_flush` | Persist pending writes to disk | — |
+| `wax_stats` | Check memory system state | — |
+
+### When to Write (`wax_remember`)
+
+Call `wax_remember` at these mandatory checkpoints:
+
+- **Plan start** — Store the plan outline before beginning implementation
+- **Task completion** — Record what was done, files changed, and outcome
+- **Key decisions** — Capture rationale for architectural or design choices
+- **Discoveries** — Log unexpected findings, gotchas, or codebase patterns
+- **Errors and fixes** — Record root cause + fix so future sessions don't re-investigate
+- **To-do items** — Store deferred work and open questions before context compacts
+
+### When to Read (`wax_recall` / `wax_search`)
+
+Call `wax_recall` or `wax_search` at these mandatory checkpoints:
+
+- **Session start** — Query for recent context on the current project before doing any work
+- **Before planning** — Check for prior plans, decisions, and deferred items
+- **Context feels stale** — When unsure about earlier decisions or state, query rather than guess
+- **Resuming interrupted work** — Always recall before continuing a previously paused task
+
+### Metadata Convention
+
+Always include these metadata keys for searchability:
+
+```json
+{
+  "project": "<project-name>",
+  "type": "plan | decision | discovery | bugfix | todo | completion",
+  "phase": "planning | implementing | reviewing | debugging"
+}
+```
+
+### Flush Discipline
+
+Call `wax_flush` to ensure writes are durable:
+
+- After storing 3+ memories in sequence
+- Before ending a session or switching projects
+- Before any operation that may trigger context compaction
+- After storing critical decisions or error resolutions

Sources/Hive/Sources/HiveCheckpointWax/CLAUDE.md

@@ -3,9 +3,5 @@
 
 <!-- This section is auto-generated by claude-mem. Edit content outside the tags. -->
 
-### Feb 10, 2026
-
-| ID | Time | T | Title | Read |
-|----|------|---|-------|------|
-| #3889 | 1:51 PM | 🔵 | HiveCheckpointWaxStore Implementation | ~559 |
+*No recent activity*
 </claude-mem-context>

Sources/Hive/Sources/HiveConduit/CLAUDE.md

@@ -3,9 +3,5 @@
 
 <!-- This section is auto-generated by claude-mem. Edit content outside the tags. -->
 
-### Feb 9, 2026
-
-| ID | Time | T | Title | Read |
-|----|------|---|-------|------|
-| #1009 | 1:02 AM | 🔵 | HiveConduit Module Structure Mirrors HiveDSL Pattern | ~358 |
+*No recent activity*
 </claude-mem-context>

Sources/Hive/Sources/HiveCore/CLAUDE.md

@@ -3,9 +3,5 @@
 
 <!-- This section is auto-generated by claude-mem. Edit content outside the tags. -->
 
-### Feb 10, 2026
-
-| ID | Time | T | Title | Read |
-|----|------|---|-------|------|
-| #3191 | 4:11 AM | 🔵 | HiveCore Mental Model and Usage Patterns | ~478 |
+*No recent activity*
 </claude-mem-context>

Sources/Hive/Sources/HiveCore/Checkpointing/CLAUDE.md

@@ -3,9 +3,5 @@
 
 <!-- This section is auto-generated by claude-mem. Edit content outside the tags. -->
 
-### Feb 10, 2026
-
-| ID | Time | T | Title | Read |
-|----|------|---|-------|------|
-| #3881 | 1:49 PM | 🔵 | Hive Checkpoint System Complete Implementation | ~593 |
+*No recent activity*
 </claude-mem-context>

Sources/Hive/Sources/HiveCore/DataStructures/HiveBitset.swift

@@ -0,0 +1,43 @@
+/// Compact dynamic bitset backed by 64-bit machine words.
+///
+/// The bitset size is fixed at initialization by `wordCount`.
+struct HiveBitset: Sendable, Equatable {
+    private var words: [UInt64]
+
+    init(wordCount: Int) {
+        self.words = Array(repeating: 0, count: max(wordCount, 0))
+    }
+
+    init(bitCapacity: Int) {
+        let wordsNeeded = max((max(bitCapacity, 0) + 63) / 64, 1)
+        self.init(wordCount: wordsNeeded)
+    }
+
+    var isEmpty: Bool {
+        words.allSatisfy { $0 == 0 }
+    }
+
+    mutating func removeAll() {
+        for index in words.indices {
+            words[index] = 0
+        }
+    }
+
+    mutating func insert(_ bitIndex: Int) {
+        guard let location = wordLocation(for: bitIndex) else { return }
+        words[location.word] |= location.mask
+    }
+
+    func contains(_ bitIndex: Int) -> Bool {
+        guard let location = wordLocation(for: bitIndex) else { return false }
+        return (words[location.word] & location.mask) != 0
+    }
+
+    private func wordLocation(for bitIndex: Int) -> (word: Int, mask: UInt64)? {
+        guard bitIndex >= 0 else { return nil }
+        let word = bitIndex / 64
+        guard words.indices.contains(word) else { return nil }
+        let bitOffset = bitIndex % 64
+        return (word: word, mask: UInt64(1) << UInt64(bitOffset))
+    }
+}

Sources/Hive/Sources/HiveCore/DataStructures/HiveInvertedIndex.swift

@@ -0,0 +1,103 @@
+import Foundation
+
+/// Lightweight BM25-style inverted index for in-memory recall.
+struct HiveInvertedIndex: Sendable {
+    private(set) var postingsByTerm: [String: [String: Int]] = [:]
+    private(set) var termFrequenciesByDocID: [String: [String: Int]] = [:]
+    private(set) var docLengthByDocID: [String: Int] = [:]
+    private(set) var totalDocLength: Int = 0
+
+    var totalDocs: Int {
+        docLengthByDocID.count
+    }
+
+    var avgDocLength: Double {
+        guard totalDocs > 0 else { return 0 }
+        return Double(totalDocLength) / Double(totalDocs)
+    }
+
+    mutating func upsert(docID: String, text: String) {
+        if docLengthByDocID[docID] != nil {
+            remove(docID: docID)
+        }
+
+        let terms = Self.tokenize(text)
+        let termFrequencies = Self.termFrequencies(terms)
+        termFrequenciesByDocID[docID] = termFrequencies
+        docLengthByDocID[docID] = terms.count
+        totalDocLength += terms.count
+
+        for (term, frequency) in termFrequencies {
+            postingsByTerm[term, default: [:]][docID] = frequency
+        }
+    }
+
+    mutating func remove(docID: String) {
+        guard let termFrequencies = termFrequenciesByDocID.removeValue(forKey: docID),
+              let length = docLengthByDocID.removeValue(forKey: docID) else {
+            return
+        }
+
+        totalDocLength -= length
+        for term in termFrequencies.keys {
+            postingsByTerm[term]?[docID] = nil
+            if postingsByTerm[term]?.isEmpty == true {
+                postingsByTerm[term] = nil
+            }
+        }
+    }
+
+    func query(terms: [String], limit: Int) -> [(docID: String, score: Double)] {
+        guard limit > 0 else { return [] }
+        guard totalDocs > 0 else { return [] }
+        guard terms.isEmpty == false else { return [] }
+
+        let k1 = 1.2
+        let b = 0.75
+        let avgdl = max(avgDocLength, 1e-9)
+        let normalizedTerms = terms.map { $0.lowercased() }
+
+        var scoresByDocID: [String: Double] = [:]
+        for term in normalizedTerms {
+            guard let postings = postingsByTerm[term], postings.isEmpty == false else { continue }
+
+            let docFrequency = postings.count
+            let idf = log(1.0 + ((Double(totalDocs - docFrequency) + 0.5) / (Double(docFrequency) + 0.5)))
+            for (docID, termFrequency) in postings {
+                let tf = Double(termFrequency)
+                let docLength = Double(docLengthByDocID[docID] ?? 0)
+                let denominator = tf + k1 * (1.0 - b + b * (docLength / avgdl))
+                guard denominator > 0 else { continue }
+                let score = idf * ((tf * (k1 + 1.0)) / denominator)
+                scoresByDocID[docID, default: 0] += score
+            }
+        }
+
+        return scoresByDocID
+            .filter { $0.value > 0 }
+            .sorted { lhs, rhs in
+                if lhs.value == rhs.value {
+                    return HiveOrdering.lexicographicallyPrecedes(lhs.key, rhs.key)
+                }
+                return lhs.value > rhs.value
+            }
+            .prefix(limit)
+            .map { (docID: $0.key, score: $0.value) }
+    }
+
+    static func tokenize(_ text: String) -> [String] {
+        text
+            .lowercased()
+            .split(whereSeparator: { $0.isLetter == false && $0.isNumber == false })
+            .map(String.init)
+    }
+
+    private static func termFrequencies(_ terms: [String]) -> [String: Int] {
+        var frequencies: [String: Int] = [:]
+        frequencies.reserveCapacity(terms.count)
+        for term in terms {
+            frequencies[term, default: 0] += 1
+        }
+        return frequencies
+    }
+}

Sources/Hive/Sources/HiveCore/Errors/HiveRuntimeError.swift

@@ -19,6 +19,7 @@ public enum HiveRuntimeError: Error, Sendable {
     case checkpointCorrupt(field: String, errorDescription: String)
     case interruptPending(interruptID: HiveInterruptID)
     case noCheckpointToResume
+    case checkpointNotFound(id: HiveCheckpointID)
     case noInterruptToResume
     case resumeInterruptMismatch(expected: HiveInterruptID, found: HiveInterruptID)
 

Sources/Hive/Sources/HiveCore/Graph/CLAUDE.md

@@ -3,5 +3,9 @@
 
 <!-- This section is auto-generated by claude-mem. Edit content outside the tags. -->
 
-*No recent activity*
+### Feb 19, 2026
+
+| ID | Time | T | Title | Read |
+|----|------|---|-------|------|
+| #7531 | 3:32 AM | 🔵 | Hive Framework: Complete Codebase Inventory | ~919 |
 </claude-mem-context>