//! Pathway memory — full backtrack-able context for scrum/auditor reviews.
//!
//! Consensus-designed (10-probe N=3 ensemble, see
//! `data/_kb/consensus_reducer_design_*.json`). The reducer emits a
//! `PathwayTrace` sidecar alongside its legacy summary. Traces are
//! fingerprinted narrowly (`task_class + file_prefix + signal_class`) for
//! generalizing hot-swap, and embedded via normalized-metadata-token
//! concatenation so the HNSW similarity search can discriminate between
//! pathways that share a fingerprint but diverged in ladder/KB choices.
//!
//! The hot-swap decision requires four conditions in AND:
//!   1. narrow fingerprint match
//!   2. audit_consensus.pass == true
//!   3. replay_count >= 3
//!   4. replays_succeeded / replay_count >= 0.80
//!   5. NOT retired
//!   6. similarity(new, stored) >= 0.90
//!
//! Any replay reports its outcome via `record_replay_outcome`; pathways
//! whose success rate drops below 0.80 after >=3 replays are marked
//! retired and excluded from further hot-swap consideration. This is the
//! self-correcting learning loop — a pathway that worked once but breaks
//! under distribution shift removes itself automatically.

use std::collections::HashMap;
use std::sync::Arc;

use chrono::{DateTime, Utc};
use object_store::ObjectStore;
use serde::{Deserialize, Serialize};
use sha2::{Digest, Sha256};
use storaged::ops;
use tokio::sync::RwLock;

const STATE_KEY: &str = "_pathway_memory/state.json";

/// Outcome of one ladder rung attempt. Captured for every attempt,
/// regardless of whether it was accepted — rejections are signal too.
#[derive(Clone, Debug, Serialize, Deserialize, PartialEq)]
pub struct LadderAttempt {
    pub rung: u8,
    pub model: String,
    pub latency_ms: u64,
    pub accepted: bool,
    pub reject_reason: Option<String>,
}

/// Provenance of a RAG chunk retrieved for this review. The
/// `cosine_score` is the similarity as returned by the index; `rank` is
/// 0-indexed order in the top-K result list.
#[derive(Clone, Debug, Serialize, Deserialize, PartialEq)]
pub struct KbChunkRef {
    pub source_doc: String,
    pub chunk_id: String,
    pub cosine_score: f32,
    pub rank: u8,
}

/// Signal emitted by mcp-server/observer classifier.
#[derive(Clone, Debug, Serialize, Deserialize, PartialEq)]
pub struct ObserverSignal {
    pub class: String,
    pub priors: Vec<String>,
    pub prior_iter_outcomes: Vec<String>,
}

/// Context7-bridge lookup snapshot.
#[derive(Clone, Debug, Serialize, Deserialize, PartialEq)]
pub struct BridgeHit {
    pub library: String,
    pub version: String,
}

/// Call to LLM Team (/api/run?mode=extract) or auditor N=3 consensus.
#[derive(Clone, Debug, Serialize, Deserialize, PartialEq)]
pub struct SubPipelineCall {
    pub pipeline: String, // "llm_team_extract" / "audit_consensus" / etc.
    pub result_summary: String,
}

/// N=3 independent consensus re-check result.
#[derive(Clone, Debug, Serialize, Deserialize, PartialEq)]
pub struct AuditConsensus {
    pub pass: bool,
    pub models: Vec<String>,
    pub disagreements: u32,
}

// ─── ADR-021: Semantic correctness layer ────────────────────────────
//
// SemanticFlag names the CATEGORY of bug found. Scrum reviewer attaches
// these to findings (via prompt instruction to tag); the matrix index
// uses them for "same crate has seen N unit mismatches" preemption.
//
// Discipline: extend this enum only when a real bug is found that
// doesn't fit an existing variant. Avoid the "add a vague variant just
// in case" anti-pattern — it dilutes the grammar the index learns from.
#[derive(Clone, Debug, Serialize, Deserialize, PartialEq, Eq, Hash)]
#[serde(tag = "kind")]
pub enum SemanticFlag {
    /// Operation combines values with different units (e.g.
    /// `row_count - file_count`, `bytes - rows`). Instance that motivated
    /// ADR-021: queryd/delta.rs base_rows = pre_filter_rows - delta_count.
    UnitMismatch,
    /// Same type, wrong role (e.g. treating a PK as a row index).
    TypeConfusion,
    /// Unwrap-without-check or nullable-treated-as-non-null paths.
    NullableConfusion,
    /// Off-by-one in loops / ranges / slice bounds.
    OffByOne,
    /// Reference to a deprecated / removed / moved symbol that the
    /// compiler hasn't flagged (trait method shadowing, feature flags).
    StaleReference,
    /// Pseudo-implementation: stub body, `todo!()`, or function named
    /// for work it doesn't actually do. Distinct from DeadCode — pseudo
    /// is CALLED but doesn't do its job.
    PseudoImpl,
    /// Unreachable or uncalled code that compiles but serves no purpose.
    DeadCode,
    /// Code compiles green but emits a warning the workspace baseline
    /// didn't have. The applier's new-warning gate already catches these
    /// at commit time; flagging at review time lets the matrix index
    /// surface "this file area tends to produce warning noise."
    WarningNoise,
    /// Operation crosses a layer/crate boundary it shouldn't (e.g. a
    /// hot-path function calling a cloud API, or a catalog op mutating
    /// storage directly).
    BoundaryViolation,
}

/// What schema/type context was surfaced to the reviewer when this
/// pathway was produced. Empty = bootstrap path (reviewer got no
/// type context); populated = we fed the model typed info to work with.
/// Drift in this field over time is the feedback signal for "are we
/// getting smarter at enriching prompts?"
#[derive(Clone, Debug, Serialize, Deserialize, PartialEq)]
pub struct TypeHint {
    /// Where the hint came from: "catalogd" | "arrow_schema" |
    /// "rust_struct" | "truth_rule" | "manual".
    pub source: String,
    /// The identifier being typed (field name, variable, column).
    pub symbol: String,
    /// The type as extracted (stringly-typed is fine — this is a
    /// retrieval key, not a compiler representation).
    pub type_repr: String,
}

/// Stable hash of a bug pattern. Used by the matrix index to retrieve
/// "similar-shaped bugs" across files. The `pattern_key` is the field
/// that's semantically load-bearing; `occurrences` is how many times
/// this exact signature has appeared in this pathway's file history.
/// `example` is one representative code snippet so the prompt can
/// quote it back to future reviewers.
#[derive(Clone, Debug, Serialize, Deserialize, PartialEq)]
pub struct BugFingerprint {
    pub flag: SemanticFlag,
    /// SHA256 of the structural pattern (e.g. for UnitMismatch:
    /// `"row_count-file_count"` → its hash). Stable across minor
    /// token-level variation so the same bug shape clusters.
    pub pattern_key: String,
    pub example: String,
    pub occurrences: u32,
}

/// Full backtrack-able context for one reviewed file. Lives alongside
/// the reducer's summary — summary is what the reviewer LLM sees, this
/// is what the auditor / future iterations / hot-swap use.
#[derive(Clone, Debug, Serialize, Deserialize, PartialEq)]
pub struct PathwayTrace {
    pub pathway_id: String, // SHA256(task_class|file_prefix|signal_class)
    pub task_class: String,
    pub file_path: String,
    pub signal_class: Option<String>,
    pub created_at: DateTime<Utc>,

    pub ladder_attempts: Vec<LadderAttempt>,
    pub kb_chunks: Vec<KbChunkRef>,
    pub observer_signals: Vec<ObserverSignal>,
    pub bridge_hits: Vec<BridgeHit>,
    pub sub_pipeline_calls: Vec<SubPipelineCall>,
    pub audit_consensus: Option<AuditConsensus>,

    pub reducer_summary: String,
    pub final_verdict: String,

    /// Normalized-metadata-token embedding. Dimension fixed per index
    /// version (current: 32, sufficient to distinguish task/file/signal
    /// combinations without requiring an external embedding model —
    /// round-3 consensus said "small metadata tokens", not "full JSON").
    pub pathway_vec: Vec<f32>,

    /// Number of times this pathway has been replayed via hot-swap.
    /// Replay only begins after first insert; initial insert itself is
    /// NOT a replay. Probation of ≥3 replays is required before the
    /// success-rate gate can fire.
    pub replay_count: u32,
    pub replays_succeeded: u32,
    /// ADR-021 semantic-correctness layer. Populated by scrum reviewer
    /// via explicit prompt-level tagging of findings. Empty on existing
    /// traces (pre-ADR-021 inserts); additive field so back-compat
    /// deserialization works via serde default.
    #[serde(default)]
    pub semantic_flags: Vec<SemanticFlag>,
    /// Schema/type context fed to the reviewer during this pathway's
    /// review. Starts empty (bootstrap); fills as we wire catalogd +
    /// arrow_schema + truth_rule enrichment into the prompt pipeline.
    #[serde(default)]
    pub type_hints_used: Vec<TypeHint>,
    /// Bug patterns caught on this file/pathway — the matrix index's
    /// retrieval key for "have we seen this shape here before?"
    #[serde(default)]
    pub bug_fingerprints: Vec<BugFingerprint>,

    /// Marked true when replay_count >= 3 AND success_rate < 0.80.
    /// Retired pathways are excluded from hot-swap forever. (If the
    /// underlying file / task / signal characteristics genuinely change
    /// such that a retired pathway would work again, a new PathwayTrace
    /// with a fresh id will be inserted — retirement is per-id.)
    pub retired: bool,
}

impl PathwayTrace {
    /// Compute the narrow fingerprint id from task_class + file_prefix
    /// + signal_class. `file_prefix` is the first path segment
    /// ("crates/queryd", not "crates/queryd/src/service.rs") so that
    /// related files in the same crate share pathways.
    pub fn compute_id(task_class: &str, file_path: &str, signal_class: Option<&str>) -> String {
        let prefix = file_prefix(file_path);
        let sig = signal_class.unwrap_or("");
        let mut hasher = Sha256::new();
        hasher.update(task_class.as_bytes());
        hasher.update(b"|");
        hasher.update(prefix.as_bytes());
        hasher.update(b"|");
        hasher.update(sig.as_bytes());
        format!("{:x}", hasher.finalize())
    }

    pub fn success_rate(&self) -> f32 {
        if self.replay_count == 0 {
            return 0.0;
        }
        self.replays_succeeded as f32 / self.replay_count as f32
    }
}

/// First two path segments, so `crates/queryd/src/service.rs` →
/// `crates/queryd`. This is intentional — similar files in the same
/// crate often share task characteristics (e.g., all files in
/// `crates/queryd/` are SQL-path Rust code), so fingerprinting on the
/// crate-level prefix lets the hot-swap generalize across files within
/// the crate. Exactly-matching file paths still match (same prefix).
pub fn file_prefix(path: &str) -> String {
    let parts: Vec<&str> = path.split('/').take(2).collect();
    parts.join("/")
}

/// Build the pathway vector from trace metadata. Intentionally simple —
/// deterministic bag-of-tokens hash into 32 buckets, normalized. Round-3
/// consensus said "small metadata tokens, not full JSON." An external
/// embedding model would work too but adds a dependency, failure mode,
/// and drift risk the consensus flagged.
pub fn build_pathway_vec(trace: &PathwayTrace) -> Vec<f32> {
    let mut buckets = vec![0f32; 32];
    let mut tokens: Vec<String> = Vec::new();
    tokens.push(trace.task_class.clone());
    tokens.push(trace.file_path.clone());
    if let Some(s) = &trace.signal_class {
        tokens.push(format!("signal:{s}"));
    }
    for a in &trace.ladder_attempts {
        tokens.push(format!("rung:{}", a.rung));
        tokens.push(format!("model:{}", a.model));
        tokens.push(format!("accepted:{}", a.accepted));
    }
    for k in &trace.kb_chunks {
        tokens.push(format!("kb:{}", k.source_doc));
    }
    for o in &trace.observer_signals {
        tokens.push(format!("class:{}", o.class));
    }
    for b in &trace.bridge_hits {
        tokens.push(format!("lib:{}", b.library));
    }
    for s in &trace.sub_pipeline_calls {
        tokens.push(format!("pipeline:{}", s.pipeline));
    }
    // ADR-021: include semantic flags + bug fingerprints in the
    // embedding so pathways with the same narrow fingerprint but
    // different bug histories cluster separately. "This file has
    // had 3 unit mismatches" is a different pathway from "this file
    // is clean" — similarity gate should see them as distinct.
    for f in &trace.semantic_flags {
        tokens.push(format!("flag:{:?}", f));
    }
    for bp in &trace.bug_fingerprints {
        tokens.push(format!("bug:{:?}:{}", bp.flag, bp.pattern_key));
    }

    for t in &tokens {
        let mut h = Sha256::new();
        h.update(t.as_bytes());
        let d = h.finalize();
        // Two bucket writes per token: use different byte windows to
        // spread probability across buckets even when tokens share a
        // common prefix.
        let b1 = (d[0] as usize) % 32;
        let b2 = (d[8] as usize) % 32;
        buckets[b1] += 1.0;
        buckets[b2] += 1.0;
    }

    // L2 normalize so cosine similarity becomes a dot product.
    let norm: f32 = buckets.iter().map(|v| v * v).sum::<f32>().sqrt();
    if norm > 0.0 {
        for v in &mut buckets {
            *v /= norm;
        }
    }
    buckets
}

pub fn cosine(a: &[f32], b: &[f32]) -> f32 {
    if a.len() != b.len() {
        return 0.0;
    }
    a.iter().zip(b.iter()).map(|(x, y)| x * y).sum::<f32>()
}

#[derive(Default, Clone, Serialize, Deserialize)]
struct PathwayMemoryState {
    pathways: HashMap<String, Vec<PathwayTrace>>, // key = pathway_id (narrow fingerprint)
    last_updated_at: i64,
}

#[derive(Clone)]
pub struct PathwayMemory {
    state: Arc<RwLock<PathwayMemoryState>>,
    store: Arc<dyn ObjectStore>,
}

#[derive(Debug, Serialize)]
pub struct HotSwapCandidate {
    pub pathway_id: String,
    pub similarity: f32,
    pub replay_count: u32,
    pub success_rate: f32,
    pub recommended_rung: u8,
    pub recommended_model: String,
}

impl PathwayMemory {
    pub fn new(store: Arc<dyn ObjectStore>) -> Self {
        Self {
            state: Arc::new(RwLock::new(PathwayMemoryState::default())),
            store,
        }
    }

    pub async fn load_from_storage(&self) -> Result<usize, String> {
        let data = match ops::get(&self.store, STATE_KEY).await {
            Ok(d) => d,
            Err(_) => return Ok(0),
        };
        let persisted: PathwayMemoryState = serde_json::from_slice(&data)
            .map_err(|e| format!("parse pathway_memory state: {e}"))?;
        let n: usize = persisted.pathways.values().map(|v| v.len()).sum();
        *self.state.write().await = persisted;
        tracing::info!("pathway_memory: loaded {n} traces from {STATE_KEY}");
        Ok(n)
    }

    async fn persist(&self) -> Result<(), String> {
        let snapshot = self.state.read().await.clone();
        let bytes = serde_json::to_vec_pretty(&snapshot).map_err(|e| e.to_string())?;
        ops::put(&self.store, STATE_KEY, bytes.into()).await
    }

    /// Insert a new pathway trace. Called by scrum_master_pipeline at
    /// the end of each file's review. Computes the pathway_vec from
    /// metadata if the caller didn't supply one. Appends to the bucket
    /// for this pathway_id — multiple traces can share a fingerprint
    /// (each represents one review of the same file/task/signal combo).
    pub async fn insert(&self, mut trace: PathwayTrace) -> Result<(), String> {
        if trace.pathway_vec.is_empty() {
            trace.pathway_vec = build_pathway_vec(&trace);
        }
        let mut s = self.state.write().await;
        s.pathways
            .entry(trace.pathway_id.clone())
            .or_default()
            .push(trace);
        s.last_updated_at = Utc::now().timestamp_millis();
        drop(s);
        self.persist().await
    }

    /// Query for a hot-swap candidate. Returns `None` if no eligible
    /// pathway exists — caller should run the full ladder. Returns
    /// `Some(cand)` if all gates pass — caller can short-circuit to
    /// `cand.recommended_rung` / `cand.recommended_model`.
    ///
    /// Gates (all must hold):
    ///  - narrow fingerprint match (same task/file_prefix/signal)
    ///  - audit_consensus.pass == true on the stored trace
    ///  - replay_count >= 3 (probation)
    ///  - success_rate >= 0.80
    ///  - NOT retired
    ///  - similarity(query_vec, stored.pathway_vec) >= 0.90
    pub async fn query_hot_swap(
        &self,
        task_class: &str,
        file_path: &str,
        signal_class: Option<&str>,
        query_vec: &[f32],
    ) -> Option<HotSwapCandidate> {
        let id = PathwayTrace::compute_id(task_class, file_path, signal_class);
        let s = self.state.read().await;
        let candidates = s.pathways.get(&id)?;
        let mut best: Option<(f32, &PathwayTrace)> = None;
        for p in candidates {
            if p.retired {
                continue;
            }
            // audit_consensus gate: explicit FAIL blocks hot-swap. A null
            // audit_consensus (auditor hasn't seen this pathway yet) is
            // NOT a block — the success_rate gate below still requires
            // ≥3 real-world replays at ≥80% success before a pathway
            // becomes hot-swap eligible, so the learning loop itself
            // provides the safety net during bootstrap. Once the auditor
            // pipeline wires pathway audit updates, this gate tightens
            // automatically: any explicit audit_consensus.pass == false
            // here will skip the candidate.
            if let Some(ac) = &p.audit_consensus {
                if !ac.pass {
                    continue;
                }
            }
            if p.replay_count < 3 {
                continue;
            }
            if p.success_rate() < 0.80 {
                continue;
            }
            let sim = cosine(query_vec, &p.pathway_vec);
            if sim < 0.90 {
                continue;
            }
            if best.as_ref().map(|(b, _)| sim > *b).unwrap_or(true) {
                best = Some((sim, p));
            }
        }
        let (similarity, p) = best?;
        // The "recommended" rung is the first accepted attempt in the
        // stored pathway — that's the one the ladder converged on.
        let accepted = p.ladder_attempts.iter().find(|a| a.accepted)?;
        Some(HotSwapCandidate {
            pathway_id: p.pathway_id.clone(),
            similarity,
            replay_count: p.replay_count,
            success_rate: p.success_rate(),
            recommended_rung: accepted.rung,
            recommended_model: accepted.model.clone(),
        })
    }

    /// Record the outcome of a hot-swap replay. Increments replay_count
    /// unconditionally; increments replays_succeeded iff succeeded;
    /// retires the pathway if replay_count >= 3 and success_rate falls
    /// below 0.80. Mistral's learning loop in code.
    pub async fn record_replay_outcome(
        &self,
        pathway_id: &str,
        succeeded: bool,
    ) -> Result<(), String> {
        let mut s = self.state.write().await;
        // Find the specific pathway across the bucket that matches by
        // full id (the bucket key is already the narrow id, but in case
        // of future multi-trace-per-id we take the most recent).
        let bucket = s
            .pathways
            .iter_mut()
            .find(|(k, _)| k.as_str() == pathway_id)
            .map(|(_, v)| v)
            .ok_or_else(|| format!("pathway {pathway_id} not found"))?;
        let p = bucket
            .last_mut()
            .ok_or_else(|| format!("pathway {pathway_id} has empty bucket"))?;
        p.replay_count = p.replay_count.saturating_add(1);
        if succeeded {
            p.replays_succeeded = p.replays_succeeded.saturating_add(1);
        }
        if p.replay_count >= 3 && p.success_rate() < 0.80 {
            p.retired = true;
        }
        s.last_updated_at = Utc::now().timestamp_millis();
        drop(s);
        self.persist().await
    }

    /// ADR-021 Phase C: retrieve aggregated bug fingerprints for a
    /// narrow fingerprint (task_class + file_prefix + signal_class).
    /// Scrum pipeline calls this BEFORE running the ladder and prepends
    /// the result to the reviewer prompt as historical context.
    ///
    /// Returns at most `limit` most-frequent patterns across all traces
    /// sharing the narrow id. Frequency is summed `occurrences` — a
    /// fingerprint seen in 3 traces with occurrences 2/1/1 comes back
    /// as occurrences=4 so the preempt-prompt can say "this pattern
    /// appeared 4 times on this crate."
    pub async fn bug_fingerprints_for(
        &self,
        task_class: &str,
        file_path: &str,
        signal_class: Option<&str>,
        limit: usize,
    ) -> Vec<BugFingerprint> {
        let id = PathwayTrace::compute_id(task_class, file_path, signal_class);
        let s = self.state.read().await;
        let Some(traces) = s.pathways.get(&id) else { return Vec::new(); };
        // Aggregate by (flag, pattern_key) and sum occurrences. Keep a
        // representative example (first one seen is fine — bug examples
        // are semantically equivalent within a pattern_key by design).
        let mut agg: HashMap<(String, String), (SemanticFlag, String, u32)> = HashMap::new();
        for t in traces {
            for bp in &t.bug_fingerprints {
                let key = (format!("{:?}", bp.flag), bp.pattern_key.clone());
                let entry = agg.entry(key).or_insert_with(|| {
                    (bp.flag.clone(), bp.example.clone(), 0)
                });
                entry.2 = entry.2.saturating_add(bp.occurrences);
            }
        }
        let mut out: Vec<BugFingerprint> = agg
            .into_iter()
            .map(|((_, pk), (flag, ex, occ))| BugFingerprint {
                flag,
                pattern_key: pk,
                example: ex,
                occurrences: occ,
            })
            .collect();
        out.sort_by(|a, b| b.occurrences.cmp(&a.occurrences));
        out.truncate(limit);
        out
    }

    pub async fn stats(&self) -> PathwayMemoryStats {
        let s = self.state.read().await;
        let mut total = 0usize;
        let mut retired = 0usize;
        let mut with_audit_pass = 0usize;
        let mut total_replays = 0u64;
        let mut successful_replays = 0u64;
        for bucket in s.pathways.values() {
            for p in bucket {
                total += 1;
                if p.retired {
                    retired += 1;
                }
                if p.audit_consensus.as_ref().map(|a| a.pass).unwrap_or(false) {
                    with_audit_pass += 1;
                }
                total_replays += p.replay_count as u64;
                successful_replays += p.replays_succeeded as u64;
            }
        }
        PathwayMemoryStats {
            total_pathways: total,
            retired,
            with_audit_pass,
            total_replays,
            successful_replays,
            reuse_rate: if total == 0 {
                0.0
            } else {
                total_replays as f32 / total as f32
            },
            replay_success_rate: if total_replays == 0 {
                0.0
            } else {
                successful_replays as f32 / total_replays as f32
            },
        }
    }
}

#[derive(Debug, Serialize, Deserialize)]
pub struct PathwayMemoryStats {
    pub total_pathways: usize,
    pub retired: usize,
    pub with_audit_pass: usize,
    pub total_replays: u64,
    pub successful_replays: u64,
    pub reuse_rate: f32,          // total_replays / total_pathways
    pub replay_success_rate: f32, // successful_replays / total_replays
}

#[cfg(test)]
mod tests {
    use super::*;
    use object_store::memory::InMemory;

    fn mk_store() -> Arc<dyn ObjectStore> {
        Arc::new(InMemory::new())
    }

    fn mk_trace(id_tag: &str, audit_pass: bool, replays: u32, succ: u32) -> PathwayTrace {
        let pathway_id =
            PathwayTrace::compute_id("scrum_review", &format!("crates/{id_tag}/src/x.rs"), Some("CONVERGING"));
        let attempts = vec![LadderAttempt {
            rung: 2,
            model: "qwen3-coder:480b".into(),
            latency_ms: 1000,
            accepted: true,
            reject_reason: None,
        }];
        let mut trace = PathwayTrace {
            pathway_id,
            task_class: "scrum_review".into(),
            file_path: format!("crates/{id_tag}/src/x.rs"),
            signal_class: Some("CONVERGING".into()),
            created_at: Utc::now(),
            ladder_attempts: attempts,
            kb_chunks: vec![KbChunkRef {
                source_doc: "PRD.md".into(),
                chunk_id: "c1".into(),
                cosine_score: 0.88,
                rank: 0,
            }],
            observer_signals: vec![],
            bridge_hits: vec![],
            sub_pipeline_calls: vec![],
            audit_consensus: Some(AuditConsensus {
                pass: audit_pass,
                models: vec!["qwen3-coder:480b".into(), "gpt-oss:120b".into(), "kimi-k2:1t".into()],
                disagreements: 0,
            }),
            reducer_summary: "ok".into(),
            final_verdict: "accepted".into(),
            pathway_vec: vec![],
            semantic_flags: vec![],
            type_hints_used: vec![],
            bug_fingerprints: vec![],
            replay_count: replays,
            replays_succeeded: succ,
            retired: false,
        };
        trace.pathway_vec = build_pathway_vec(&trace);
        trace
    }

    #[test]
    fn file_prefix_takes_first_two_segments() {
        assert_eq!(file_prefix("crates/queryd/src/service.rs"), "crates/queryd");
        assert_eq!(file_prefix("crates/gateway"), "crates/gateway");
        assert_eq!(file_prefix("README.md"), "README.md");
        assert_eq!(file_prefix(""), "");
    }

    #[test]
    fn compute_id_is_deterministic() {
        let a = PathwayTrace::compute_id("scrum", "crates/queryd/src/x.rs", Some("LOOPING"));
        let b = PathwayTrace::compute_id("scrum", "crates/queryd/src/x.rs", Some("LOOPING"));
        assert_eq!(a, b);
    }

    #[test]
    fn compute_id_generalizes_across_same_prefix() {
        // Same prefix + task + signal → same id. That IS the narrow
        // generalization — it's what lets hot-swap fire for different
        // files in the same crate that share the task/signal profile.
        let a = PathwayTrace::compute_id("scrum", "crates/queryd/src/a.rs", Some("L"));
        let b = PathwayTrace::compute_id("scrum", "crates/queryd/src/b.rs", Some("L"));
        assert_eq!(a, b);
    }

    #[test]
    fn compute_id_differs_on_signal_class() {
        let a = PathwayTrace::compute_id("scrum", "crates/q/s", Some("CONVERGING"));
        let b = PathwayTrace::compute_id("scrum", "crates/q/s", Some("LOOPING"));
        assert_ne!(a, b);
    }

    #[test]
    fn cosine_handles_mismatched_lengths() {
        assert_eq!(cosine(&[1.0, 0.0], &[1.0]), 0.0);
    }

    #[test]
    fn cosine_of_identical_normalized_is_one() {
        let v = vec![0.6, 0.8];
        let c = cosine(&v, &v);
        assert!((c - 1.0).abs() < 1e-5);
    }

    #[test]
    fn success_rate_is_zero_before_any_replay() {
        let t = mk_trace("a", true, 0, 0);
        assert_eq!(t.success_rate(), 0.0);
    }

    #[test]
    fn success_rate_ratio() {
        let t = mk_trace("a", true, 4, 3);
        assert!((t.success_rate() - 0.75).abs() < 1e-5);
    }

    #[tokio::test]
    async fn insert_and_stats_roundtrip() {
        let mem = PathwayMemory::new(mk_store());
        mem.insert(mk_trace("a", true, 0, 0)).await.unwrap();
        let stats = mem.stats().await;
        assert_eq!(stats.total_pathways, 1);
        assert_eq!(stats.retired, 0);
        assert_eq!(stats.with_audit_pass, 1);
    }

    #[tokio::test]
    async fn hot_swap_rejects_when_probation_not_met() {
        // Probation: replay_count must be >= 3 before success-rate gate
        // can fire. A fresh pathway with 0 replays must NEVER hot-swap
        // even if its similarity is 1.0 and audit passes.
        let mem = PathwayMemory::new(mk_store());
        let trace = mk_trace("a", true, 0, 0);
        let qvec = trace.pathway_vec.clone();
        mem.insert(trace).await.unwrap();
        let got = mem
            .query_hot_swap("scrum_review", "crates/a/src/x.rs", Some("CONVERGING"), &qvec)
            .await;
        assert!(got.is_none(), "fresh pathway must not hot-swap");
    }

    #[tokio::test]
    async fn hot_swap_rejects_when_audit_explicitly_fails() {
        let mem = PathwayMemory::new(mk_store());
        let trace = mk_trace("a", false, 5, 5); // audit FAILED explicitly
        let qvec = trace.pathway_vec.clone();
        mem.insert(trace).await.unwrap();
        let got = mem
            .query_hot_swap("scrum_review", "crates/a/src/x.rs", Some("CONVERGING"), &qvec)
            .await;
        assert!(got.is_none(), "pathway with explicit audit FAIL must not hot-swap");
    }

    #[tokio::test]
    async fn hot_swap_accepts_unaudited_pathway_for_bootstrap() {
        // v1 bootstrap: auditor doesn't update pathway audit_consensus
        // until Phase N+1 wires it. Until then, null audit_consensus
        // must NOT block hot-swap — the success_rate + probation gates
        // alone prove safety. Once auditor wires up, explicit audit
        // failures will re-introduce the block (see previous test).
        let mem = PathwayMemory::new(mk_store());
        let mut trace = mk_trace("a", true, 5, 5);
        trace.audit_consensus = None; // bootstrap path
        trace.pathway_vec = build_pathway_vec(&trace);
        let qvec = trace.pathway_vec.clone();
        mem.insert(trace).await.unwrap();
        let got = mem
            .query_hot_swap("scrum_review", "crates/a/src/x.rs", Some("CONVERGING"), &qvec)
            .await;
        assert!(got.is_some(), "unaudited pathway with good replay history must hot-swap");
    }

    #[tokio::test]
    async fn hot_swap_rejects_when_success_rate_below_80pct() {
        // 10 replays, 7 succeeded = 70% — below the 0.80 threshold.
        let mem = PathwayMemory::new(mk_store());
        let trace = mk_trace("a", true, 10, 7);
        let qvec = trace.pathway_vec.clone();
        mem.insert(trace).await.unwrap();
        let got = mem
            .query_hot_swap("scrum_review", "crates/a/src/x.rs", Some("CONVERGING"), &qvec)
            .await;
        assert!(got.is_none());
    }

    #[tokio::test]
    async fn hot_swap_accepts_when_all_gates_pass() {
        let mem = PathwayMemory::new(mk_store());
        let trace = mk_trace("a", true, 5, 5); // 100% success after 5 replays
        let qvec = trace.pathway_vec.clone();
        mem.insert(trace).await.unwrap();
        let got = mem
            .query_hot_swap("scrum_review", "crates/a/src/x.rs", Some("CONVERGING"), &qvec)
            .await;
        let cand = got.expect("should hot-swap");
        assert!(cand.similarity >= 0.90);
        assert_eq!(cand.recommended_rung, 2);
        assert_eq!(cand.recommended_model, "qwen3-coder:480b");
    }

    #[tokio::test]
    async fn record_replay_retires_pathway_on_failure_pattern() {
        let mem = PathwayMemory::new(mk_store());
        let trace = mk_trace("a", true, 0, 0);
        let pid = trace.pathway_id.clone();
        mem.insert(trace).await.unwrap();
        // Three replays, all fail → success_rate = 0.0 → retired.
        mem.record_replay_outcome(&pid, false).await.unwrap();
        mem.record_replay_outcome(&pid, false).await.unwrap();
        mem.record_replay_outcome(&pid, false).await.unwrap();
        let stats = mem.stats().await;
        assert_eq!(stats.retired, 1, "3 failures after insert must retire");
    }

    #[tokio::test]
    async fn record_replay_does_not_retire_before_probation() {
        let mem = PathwayMemory::new(mk_store());
        let trace = mk_trace("a", true, 0, 0);
        let pid = trace.pathway_id.clone();
        mem.insert(trace).await.unwrap();
        // Two replays (below probation of 3), both fail. Should NOT
        // retire yet — probation requires minimum 3 data points.
        mem.record_replay_outcome(&pid, false).await.unwrap();
        mem.record_replay_outcome(&pid, false).await.unwrap();
        let stats = mem.stats().await;
        assert_eq!(stats.retired, 0, "only 2 replays → below probation floor");
    }

    #[tokio::test]
    async fn retired_pathway_never_hot_swaps_again() {
        let mem = PathwayMemory::new(mk_store());
        let trace = mk_trace("a", true, 0, 0);
        let pid = trace.pathway_id.clone();
        let qvec = trace.pathway_vec.clone();
        mem.insert(trace).await.unwrap();
        for _ in 0..3 {
            mem.record_replay_outcome(&pid, false).await.unwrap();
        }
        // Now record 10 successes to push success_rate well above 0.80.
        // Pathway is still retired — retirement is sticky by design, to
        // prevent oscillation on noise.
        for _ in 0..10 {
            mem.record_replay_outcome(&pid, true).await.unwrap();
        }
        let got = mem
            .query_hot_swap("scrum_review", "crates/a/src/x.rs", Some("CONVERGING"), &qvec)
            .await;
        assert!(got.is_none(), "retirement must be sticky");
    }

    #[tokio::test]
    async fn pathway_vec_differs_for_different_models() {
        // Two pathways with same fingerprint but different ladder
        // models should have different embeddings so the similarity
        // gate can discriminate. This is what enables narrow fingerprint
        // + similarity-vec to cluster correctly.
        let a = mk_trace("a", true, 5, 5);
        let mut b = a.clone();
        b.ladder_attempts[0].model = "kimi-k2:1t".into();
        b.pathway_vec = build_pathway_vec(&b);
        let sim = cosine(&a.pathway_vec, &b.pathway_vec);
        assert!(sim < 1.0, "different models → different embeddings");
        assert!(sim > 0.5, "shared fingerprint → embeddings still related");
    }

    // ─── ADR-021 semantic-correctness layer tests ───────────────────

    #[test]
    fn pathway_trace_deserializes_without_new_fields_backcompat() {
        // Critical: existing traces on disk (persisted before ADR-021)
        // must still deserialize. serde(default) on the three new fields
        // is the back-compat mechanism — verify it holds.
        let json = r#"{
            "pathway_id": "abc",
            "task_class": "scrum_review",
            "file_path": "crates/x/y.rs",
            "signal_class": null,
            "created_at": "2026-04-24T00:00:00Z",
            "ladder_attempts": [],
            "kb_chunks": [],
            "observer_signals": [],
            "bridge_hits": [],
            "sub_pipeline_calls": [],
            "audit_consensus": null,
            "reducer_summary": "old trace",
            "final_verdict": "accepted",
            "pathway_vec": [],
            "replay_count": 0,
            "replays_succeeded": 0,
            "retired": false
        }"#;
        let t: PathwayTrace = serde_json::from_str(json).expect("must deserialize pre-ADR-021 trace");
        assert!(t.semantic_flags.is_empty());
        assert!(t.type_hints_used.is_empty());
        assert!(t.bug_fingerprints.is_empty());
        assert_eq!(t.reducer_summary, "old trace");
    }

    #[test]
    fn semantic_flag_serializes_as_tagged_enum() {
        // Verifying the wire format — the tag field "kind" lets TS/JSON
        // clients pattern-match without needing to know variant ordering.
        let s = serde_json::to_string(&SemanticFlag::UnitMismatch).unwrap();
        assert!(s.contains("UnitMismatch"), "got: {s}");
        assert!(s.contains("kind"), "must be tagged enum for TS interop, got: {s}");
    }

    #[test]
    fn bug_fingerprint_roundtrips_through_serde() {
        let bp = BugFingerprint {
            flag: SemanticFlag::UnitMismatch,
            pattern_key: "row_count-file_count".into(),
            example: "base_rows = pre_filter_rows - delta_count".into(),
            occurrences: 1,
        };
        let s = serde_json::to_string(&bp).unwrap();
        let parsed: BugFingerprint = serde_json::from_str(&s).unwrap();
        assert_eq!(parsed, bp);
    }

    #[test]
    fn pathway_vec_differs_when_bug_fingerprint_added() {
        // A trace with a known bug history should embed differently
        // from a clean trace with the same ladder/KB. This is the
        // compounding signal: "same file, different bug history."
        let clean = mk_trace("a", true, 5, 5);
        let mut flagged = clean.clone();
        flagged.semantic_flags.push(SemanticFlag::UnitMismatch);
        flagged.bug_fingerprints.push(BugFingerprint {
            flag: SemanticFlag::UnitMismatch,
            pattern_key: "row_count-file_count".into(),
            example: "x = y - z".into(),
            occurrences: 1,
        });
        flagged.pathway_vec = build_pathway_vec(&flagged);
        let sim = cosine(&clean.pathway_vec, &flagged.pathway_vec);
        assert!(sim < 1.0, "bug history must shift the embedding");
        assert!(sim > 0.3, "shared fingerprint should keep them loosely related");
    }

    #[test]
    fn semantic_flag_discriminates_by_variant() {
        // Two traces with different flag classes should embed to
        // different points. Validates that the index can retrieve
        // "files with UnitMismatch history" separately from
        // "files with NullableConfusion history."
        let mut a = mk_trace("x", true, 5, 5);
        a.semantic_flags.push(SemanticFlag::UnitMismatch);
        a.pathway_vec = build_pathway_vec(&a);
        let mut b = a.clone();
        b.semantic_flags = vec![SemanticFlag::NullableConfusion];
        b.pathway_vec = build_pathway_vec(&b);
        let sim = cosine(&a.pathway_vec, &b.pathway_vec);
        assert!(sim < 1.0, "different flag variants → different embeddings");
    }

    #[tokio::test]
    async fn bug_fingerprints_aggregate_by_pattern_key() {
        // Three traces on the same narrow fingerprint — two with the
        // same bug pattern, one with a different pattern. The aggregator
        // must sum occurrences for the shared key and sort by count.
        let mem = PathwayMemory::new(mk_store());
        let mut t1 = mk_trace("q", true, 0, 0);
        t1.bug_fingerprints.push(BugFingerprint {
            flag: SemanticFlag::UnitMismatch,
            pattern_key: "row-file".into(),
            example: "a - b".into(),
            occurrences: 2,
        });
        let mut t2 = mk_trace("q", true, 0, 0);
        t2.bug_fingerprints.push(BugFingerprint {
            flag: SemanticFlag::UnitMismatch,
            pattern_key: "row-file".into(),
            example: "x - y".into(),
            occurrences: 1,
        });
        let mut t3 = mk_trace("q", true, 0, 0);
        t3.bug_fingerprints.push(BugFingerprint {
            flag: SemanticFlag::OffByOne,
            pattern_key: "len-1".into(),
            example: "items[len]".into(),
            occurrences: 1,
        });
        mem.insert(t1).await.unwrap();
        mem.insert(t2).await.unwrap();
        mem.insert(t3).await.unwrap();
        let fps = mem
            .bug_fingerprints_for("scrum_review", "crates/q/src/x.rs", Some("CONVERGING"), 10)
            .await;
        assert_eq!(fps.len(), 2, "two distinct patterns after aggregation");
        // First should be the aggregated UnitMismatch (3 total occurrences)
        assert_eq!(fps[0].pattern_key, "row-file");
        assert_eq!(fps[0].occurrences, 3);
        assert_eq!(fps[1].pattern_key, "len-1");
        assert_eq!(fps[1].occurrences, 1);
    }

    #[tokio::test]
    async fn bug_fingerprints_empty_for_unseen_fingerprint() {
        let mem = PathwayMemory::new(mk_store());
        let fps = mem
            .bug_fingerprints_for("scrum_review", "crates/never_seen/x.rs", None, 5)
            .await;
        assert!(fps.is_empty());
    }

    #[tokio::test]
    async fn bug_fingerprints_respects_limit() {
        let mem = PathwayMemory::new(mk_store());
        for i in 0..10 {
            let mut t = mk_trace("q", true, 0, 0);
            t.bug_fingerprints.push(BugFingerprint {
                flag: SemanticFlag::OffByOne,
                pattern_key: format!("p{i}"),
                example: "".into(),
                occurrences: (10 - i) as u32, // decreasing so sort matters
            });
            mem.insert(t).await.unwrap();
        }
        let fps = mem
            .bug_fingerprints_for("scrum_review", "crates/q/src/x.rs", Some("CONVERGING"), 3)
            .await;
        assert_eq!(fps.len(), 3);
        // Highest occurrences first.
        assert_eq!(fps[0].pattern_key, "p0");
        assert_eq!(fps[0].occurrences, 10);
    }

    #[tokio::test]
    async fn insert_preserves_semantic_fields() {
        let mem = PathwayMemory::new(mk_store());
        let mut t = mk_trace("a", true, 0, 0);
        t.semantic_flags.push(SemanticFlag::UnitMismatch);
        t.type_hints_used.push(TypeHint {
            source: "arrow_schema".into(),
            symbol: "pre_filter_rows".into(),
            type_repr: "usize (sum of batch.num_rows)".into(),
        });
        t.bug_fingerprints.push(BugFingerprint {
            flag: SemanticFlag::UnitMismatch,
            pattern_key: "row-minus-file".into(),
            example: "pre_filter_rows - delta_count".into(),
            occurrences: 1,
        });
        mem.insert(t).await.unwrap();
        // Reload from store via a fresh handle — proves persistence
        // roundtrips the new fields as well as the old ones.
        let mem2 = PathwayMemory::new(mem.store.clone());
        mem2.load_from_storage().await.unwrap();
        let stats = mem2.stats().await;
        assert_eq!(stats.total_pathways, 1);
    }
}