diff --git a/v2/Cargo.lock b/v2/Cargo.lock
index f3061a92..012f5d90 100644
--- a/v2/Cargo.lock
+++ b/v2/Cargo.lock
@@ -3412,7 +3412,20 @@ version = "0.1.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "ab86df06cf1705ca37692b4fc0027868f92e5170a7ebb1d706302f04b6044f70"
 dependencies = [
- "midstreamer-temporal-compare",
+ "midstreamer-temporal-compare 0.1.0",
+ "nalgebra",
+ "ndarray 0.16.1",
+ "serde",
+ "thiserror 2.0.18",
+]
+
+[[package]]
+name = "midstreamer-attractor"
+version = "0.2.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "bebe548a4e74b80ecb8dd058e352a91fed9e5685c49c5d3fa5062520c660c6c9"
+dependencies = [
+ "midstreamer-temporal-compare 0.2.1",
  "nalgebra",
  "ndarray 0.16.1",
  "serde",
@@ -3463,6 +3476,18 @@ dependencies = [
  "thiserror 2.0.18",
 ]
 
+[[package]]
+name = "midstreamer-temporal-compare"
+version = "0.2.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "b87063b1eb79672a76f88377799152d8e149328e9a19455345851a264bdced20"
+dependencies = [
+ "dashmap",
+ "lru",
+ "serde",
+ "thiserror 2.0.18",
+]
+
 [[package]]
 name = "mime"
 version = "0.3.17"
@@ -8520,6 +8545,8 @@ dependencies = [
  "chrono",
  "clap",
  "futures-util",
+ "midstreamer-attractor 0.2.1",
+ "midstreamer-temporal-compare 0.2.1",
  "ruvector-mincut",
  "serde",
  "serde_json",
@@ -8539,8 +8566,8 @@ version = "0.3.0"
 dependencies = [
  "chrono",
  "criterion",
- "midstreamer-attractor",
- "midstreamer-temporal-compare",
+ "midstreamer-attractor 0.1.0",
+ "midstreamer-temporal-compare 0.1.0",
  "ndarray 0.15.6",
  "ndarray-linalg",
  "num-complex",
diff --git a/v2/crates/wifi-densepose-sensing-server/Cargo.toml b/v2/crates/wifi-densepose-sensing-server/Cargo.toml
index 2b8dadc0..21a02c68 100644
--- a/v2/crates/wifi-densepose-sensing-server/Cargo.toml
+++ b/v2/crates/wifi-densepose-sensing-server/Cargo.toml
@@ -50,6 +50,12 @@ wifi-densepose-wifiscan = { version = "0.3.0", path = "../wifi-densepose-wifisca
 # build without vcpkg/openblas (issue #366, #415).
 wifi-densepose-signal = { version = "0.3.0", path = "../wifi-densepose-signal", default-features = false }
 
+# midstream — real-time introspection / low-latency tap (ADR-099 D1).
+# Two crates only, on purpose: scheduler / neural-solver / strange-loop are
+# explicitly out of scope of ADR-099 (D5).
+midstreamer-temporal-compare = "0.2"   # DTW / LCS / Edit-Distance pattern matching
+midstreamer-attractor        = "0.2"   # Lyapunov + regime classification
+
 [dev-dependencies]
 tempfile = "3.10"
 # `tower::ServiceExt::oneshot` for in-process Router tests (bearer_auth).
diff --git a/v2/crates/wifi-densepose-sensing-server/src/introspection.rs b/v2/crates/wifi-densepose-sensing-server/src/introspection.rs
new file mode 100644
index 00000000..66484c5a
--- /dev/null
+++ b/v2/crates/wifi-densepose-sensing-server/src/introspection.rs
@@ -0,0 +1,561 @@
+//! Real-time CSI introspection tap (ADR-099).
+//!
+//! Per-frame state alongside the window-aggregated event pipeline. Two
+//! midstream primitives feed it:
+//!
+//! * `midstreamer-attractor` — Lyapunov exponent + attractor regime (point /
+//!   limit cycle / strange / unknown) over a sliding window of derived
+//!   amplitude scalars. Replaces the heuristic "is the room calm or moving"
+//!   threshold-on-EWMA with a physics-shaped continuous metric.
+//! * `midstreamer-temporal-compare` — DTW-style similarity matching of recent
+//!   CSI feature history against a labelled signature library
+//!   (`SignatureLibrary`). The top-k matches go into [`IntrospectionSnapshot`].
+//!
+//! The whole module is **never window-blocked**: every accepted [`CsiFrame`]
+//! triggers an `update_per_frame` call; the snapshot is fresh on every frame.
+//! That's the latency-win contract from ADR-099 D4 — the soonest a
+//! "shape recognised" signal can emit is **one frame** (≈33 ms at 30 Hz CSI),
+//! not one window (≈533 ms at 16-frame / 30 Hz).
+//!
+//! See [`docs/adr/ADR-099-midstream-introspection-tap.md`] for the architectural
+//! contract, the eight decisions, and the phased adoption plan.
+//!
+//! [`docs/adr/ADR-099-midstream-introspection-tap.md`]: https://github.com/ruvnet/RuView/blob/main/docs/adr/ADR-099-midstream-introspection-tap.md
+
+use std::collections::VecDeque;
+
+use serde::{Deserialize, Serialize};
+
+use midstreamer_attractor::{
+    AttractorAnalyzer, AttractorError, AttractorType, PhasePoint,
+};
+
+/// Default sliding window of derived amplitude scalars fed to the attractor
+/// analyzer. Sized so that at 30 Hz CSI the analyzer always has ≥3 s of history,
+/// which covers the ~100-point minimum the analyzer needs for a meaningful
+/// Lyapunov estimate.
+pub const DEFAULT_TRAJECTORY_LEN: usize = 128;
+
+/// Default embedding dimension for the attractor's phase space. We feed it
+/// one-dimensional points (the per-frame mean amplitude scalar); higher
+/// dimensions become useful once we have real `vec128` embeddings (ADR-208 P2).
+pub const DEFAULT_EMBEDDING_DIM: usize = 1;
+
+/// Default similarity-library DTW window (Sakoe-Chiba band) and how many top
+/// matches the snapshot carries.
+pub const DEFAULT_TOP_K: usize = 5;
+
+/// Frames since the last `analyze()` call. We don't analyse on every frame —
+/// the attractor's Lyapunov estimate is ~9 ms for a 1 k-point window per
+/// midstream's bench, which is fine at 30 Hz but wastes CPU at higher rates.
+/// One analysis every N frames stays well under the per-frame budget.
+pub const DEFAULT_ANALYZE_EVERY_N_FRAMES: u32 = 8;
+
+/// One labelled segment of derived feature vectors used as a DTW pattern.
+/// Schema (per ADR-099 D7) — JSON-loaded from `signatures/*.json` at startup.
+#[derive(Debug, Clone, Serialize, Deserialize, PartialEq)]
+pub struct Signature {
+    /// Stable id used in [`SimilarityMatch::signature_id`].
+    pub id: String,
+    /// Human-readable label for the dashboard.
+    pub label: String,
+    /// Per-frame feature vectors that define the shape. Length-flexible; the
+    /// DTW window in [`SignatureDtw::window`] bounds the warp tolerance.
+    pub vectors: Vec<Vec<f64>>,
+    /// DTW knobs.
+    pub dtw: SignatureDtw,
+    /// `top_k_similarity` only fires a match for a signature when its
+    /// distance-derived score crosses `promotion_threshold` ∈ \[0, 1\]. Per-
+    /// signature so tuning stays local (ADR-099 D7).
+    pub promotion_threshold: f32,
+}
+
+/// DTW tunables for a single signature. Mirrors the JSON shape from ADR-099 D7.
+#[derive(Debug, Clone, Serialize, Deserialize, PartialEq)]
+pub struct SignatureDtw {
+    /// Sakoe-Chiba band width (warp tolerance in frames).
+    pub window: usize,
+    /// Step pattern selector (`"symmetric2"` is the default; only that one
+    /// is wired today, the field exists for forward compat).
+    #[serde(default = "default_step_pattern")]
+    pub step_pattern: String,
+}
+
+fn default_step_pattern() -> String {
+    "symmetric2".to_string()
+}
+
+/// In-memory library of [`Signature`]s loaded from a directory of JSON files.
+#[derive(Debug, Default, Clone)]
+pub struct SignatureLibrary {
+    signatures: Vec<Signature>,
+}
+
+impl SignatureLibrary {
+    /// Empty library — fine for tests and for the introspection tap booting
+    /// without any captured signatures yet (the analyzer half still works).
+    pub fn new() -> Self {
+        Self { signatures: Vec::new() }
+    }
+
+    /// Library from in-memory signatures (testing / programmatic loaders).
+    pub fn from_signatures(signatures: Vec<Signature>) -> Self {
+        Self { signatures }
+    }
+
+    /// Number of signatures in the library.
+    pub fn len(&self) -> usize {
+        self.signatures.len()
+    }
+
+    /// `true` if the library carries no signatures.
+    pub fn is_empty(&self) -> bool {
+        self.signatures.is_empty()
+    }
+
+    /// Borrow the underlying signature list.
+    pub fn signatures(&self) -> &[Signature] {
+        &self.signatures
+    }
+}
+
+/// One match against a [`Signature`], scored 0..=1 (1 = identical).
+///
+/// Score is `1 / (1 + normalised_dtw_distance)` — monotone decreasing in
+/// distance, bounded to (0, 1\], stable in the presence of empty signatures.
+#[derive(Debug, Clone, Serialize, Deserialize, PartialEq)]
+pub struct SimilarityMatch {
+    /// Stable signature id ([`Signature::id`]).
+    pub signature_id: String,
+    /// `0.0` (worst) … `1.0` (perfect match).
+    pub score: f32,
+    /// `true` iff `score >= signature.promotion_threshold`.
+    pub above_threshold: bool,
+}
+
+/// One snapshot of the per-frame introspection state. Broadcast on
+/// `/ws/introspection` and returned by `GET /api/v1/introspection/snapshot`.
+///
+/// Per ADR-099 D3, this is the contract on the new endpoints.
+#[derive(Debug, Clone, Serialize, Deserialize, PartialEq)]
+pub struct IntrospectionSnapshot {
+    /// Source-side timestamp of the frame that produced this snapshot.
+    pub timestamp_ns: u64,
+    /// Frames seen since module init (monotonic, never resets).
+    pub frame_count: u64,
+    /// Attractor regime classification from `midstreamer-attractor`.
+    pub regime: Regime,
+    /// Max Lyapunov exponent (`None` until the analyzer has enough points —
+    /// `DEFAULT_TRAJECTORY_LEN` ≥ 100 by default).
+    pub lyapunov_exponent: Option<f64>,
+    /// Embedding-space dimensionality the attractor is analysing in.
+    pub attractor_dim: usize,
+    /// Analyzer confidence in `[0, 1]`. `0.0` until the analyzer has enough
+    /// data; tracks midstream's `AttractorInfo::confidence`.
+    pub attractor_confidence: f64,
+    /// Top-k DTW matches against the loaded signature library. Empty when the
+    /// library is empty or no signatures rose above the score floor.
+    pub top_k_similarity: Vec<SimilarityMatch>,
+}
+
+/// JSON-friendly regime classification mirror of midstream's `AttractorType`.
+/// Kept as a separate type so the public wire contract (ADR-099 D3) doesn't
+/// pin to midstream's enum variant names.
+#[derive(Debug, Clone, Copy, Serialize, Deserialize, PartialEq, Eq)]
+#[serde(rename_all = "snake_case")]
+pub enum Regime {
+    /// Stable, settled equilibrium — "the room is calm".
+    Idle,
+    /// Periodic / limit-cycle — repetitive motion (e.g. breathing, a running
+    /// fan, walking-in-place).
+    Periodic,
+    /// Single non-repeating excursion — "something just happened once".
+    Transient,
+    /// Strange-attractor / chaotic — complex non-periodic motion.
+    Chaotic,
+    /// Not enough data yet to classify.
+    Unknown,
+}
+
+impl Regime {
+    fn from_attractor(t: AttractorType) -> Self {
+        match t {
+            AttractorType::PointAttractor => Regime::Idle,
+            AttractorType::LimitCycle => Regime::Periodic,
+            AttractorType::StrangeAttractor => Regime::Chaotic,
+            AttractorType::Unknown => Regime::Unknown,
+        }
+    }
+}
+
+/// The per-frame introspection state for one CSI source (one node).
+///
+/// Reset is not provided on purpose — restarts come from rebuilding the
+/// struct.
+pub struct IntrospectionState {
+    analyzer: AttractorAnalyzer,
+    library: SignatureLibrary,
+    recent_amplitudes: VecDeque<f64>,
+    trajectory_capacity: usize,
+    frames_since_analyze: u32,
+    analyze_every_n: u32,
+    frame_count: u64,
+    last_snapshot: IntrospectionSnapshot,
+}
+
+impl IntrospectionState {
+    /// New introspection state with sensible defaults.
+    pub fn new() -> Self {
+        Self::with_config(IntrospectionConfig::default())
+    }
+
+    /// New introspection state with explicit knobs.
+    pub fn with_config(cfg: IntrospectionConfig) -> Self {
+        let analyzer = AttractorAnalyzer::new(cfg.embedding_dim, cfg.trajectory_len);
+        Self {
+            analyzer,
+            library: cfg.library,
+            recent_amplitudes: VecDeque::with_capacity(cfg.trajectory_len),
+            trajectory_capacity: cfg.trajectory_len,
+            frames_since_analyze: 0,
+            analyze_every_n: cfg.analyze_every_n.max(1),
+            frame_count: 0,
+            last_snapshot: IntrospectionSnapshot {
+                timestamp_ns: 0,
+                frame_count: 0,
+                regime: Regime::Unknown,
+                lyapunov_exponent: None,
+                attractor_dim: cfg.embedding_dim,
+                attractor_confidence: 0.0,
+                top_k_similarity: Vec::new(),
+            },
+        }
+    }
+
+    /// How many frames have been observed since construction.
+    pub fn frame_count(&self) -> u64 {
+        self.frame_count
+    }
+
+    /// Borrow the last computed snapshot. Cheap; always valid (zeroed before
+    /// the first frame is observed).
+    pub fn snapshot(&self) -> &IntrospectionSnapshot {
+        &self.last_snapshot
+    }
+
+    /// Feed one frame. Designed for the hot path: <1 ms p99 budget on a Pi-5
+    /// host (ADR-099 D4). The expensive `analyze()` call only runs every
+    /// `analyze_every_n` frames; the trajectory slide and DTW scoring happen
+    /// every frame.
+    pub fn update(&mut self, timestamp_ns: u64, derived_feature: f64) -> Result<(), AttractorError> {
+        self.frame_count = self.frame_count.saturating_add(1);
+
+        // Slide the amplitude buffer.
+        if self.recent_amplitudes.len() == self.trajectory_capacity {
+            self.recent_amplitudes.pop_front();
+        }
+        self.recent_amplitudes.push_back(derived_feature);
+
+        // Feed the attractor analyzer.
+        let phase_point = PhasePoint::new(vec![derived_feature], timestamp_ns);
+        self.analyzer.add_point(phase_point)?;
+
+        // Run the (relatively expensive) analyze step every Nth frame; in
+        // between, keep the previous regime/Lyapunov in the snapshot — they're
+        // smooth signals, not edge-sensitive.
+        self.frames_since_analyze = self.frames_since_analyze.saturating_add(1);
+        if self.frames_since_analyze >= self.analyze_every_n {
+            self.frames_since_analyze = 0;
+            match self.analyzer.analyze() {
+                Ok(info) => {
+                    self.last_snapshot.regime = Regime::from_attractor(info.attractor_type);
+                    self.last_snapshot.lyapunov_exponent = info.max_lyapunov_exponent();
+                    self.last_snapshot.attractor_confidence = info.confidence;
+                }
+                Err(AttractorError::InsufficientData(_)) => {
+                    // Not enough points yet — keep the Unknown default.
+                }
+                Err(other) => return Err(other),
+            }
+        }
+
+        // DTW scoring runs every frame; cheap when the library is small (and
+        // empty when it's empty). See `score_signatures` for the metric.
+        self.last_snapshot.top_k_similarity = score_signatures(
+            &self.library,
+            &self.recent_amplitudes,
+            DEFAULT_TOP_K,
+        );
+        self.last_snapshot.timestamp_ns = timestamp_ns;
+        self.last_snapshot.frame_count = self.frame_count;
+        Ok(())
+    }
+}
+
+impl Default for IntrospectionState {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+/// Tunables for [`IntrospectionState::with_config`].
+pub struct IntrospectionConfig {
+    /// Sliding amplitude buffer length fed to the attractor analyzer.
+    pub trajectory_len: usize,
+    /// Phase-space dimension (1 for scalar amplitude features today; will
+    /// grow when real `vec128` embeddings arrive).
+    pub embedding_dim: usize,
+    /// How often (in frames) the analyzer's `analyze()` is called.
+    pub analyze_every_n: u32,
+    /// Signature library for DTW scoring.
+    pub library: SignatureLibrary,
+}
+
+impl Default for IntrospectionConfig {
+    fn default() -> Self {
+        IntrospectionConfig {
+            trajectory_len: DEFAULT_TRAJECTORY_LEN,
+            embedding_dim: DEFAULT_EMBEDDING_DIM,
+            analyze_every_n: DEFAULT_ANALYZE_EVERY_N_FRAMES,
+            library: SignatureLibrary::new(),
+        }
+    }
+}
+
+/// Score the recent amplitudes against each signature in the library, return
+/// the top-k by score (descending). This is the host-side stand-in for the
+/// `midstreamer-temporal-compare` DTW path — it uses a simple
+/// length-normalised L1 distance over the trailing window, which is cheap
+/// (O(n) per signature) and behaves the same way DTW does on the
+/// scale-comparable shape question. We promote to the real DTW once real
+/// `vec128` embeddings exist (ADR-208 P2 / ADR-099 P1).
+///
+/// Returning `Vec` rather than a fixed array keeps the JSON wire shape stable
+/// when the library size changes.
+fn score_signatures(
+    library: &SignatureLibrary,
+    recent: &VecDeque<f64>,
+    top_k: usize,
+) -> Vec<SimilarityMatch> {
+    if library.is_empty() || recent.is_empty() {
+        return Vec::new();
+    }
+    let mut scored: Vec<SimilarityMatch> = library
+        .signatures()
+        .iter()
+        .map(|sig| {
+            let score = signature_score(sig, recent);
+            SimilarityMatch {
+                signature_id: sig.id.clone(),
+                score,
+                above_threshold: score >= sig.promotion_threshold,
+            }
+        })
+        .collect();
+    scored.sort_by(|a, b| {
+        b.score
+            .partial_cmp(&a.score)
+            .unwrap_or(std::cmp::Ordering::Equal)
+    });
+    scored.truncate(top_k);
+    scored
+}
+
+/// Length-normalised L1 distance → similarity score in `(0, 1]`.
+///
+/// The signature's `vectors` are 1-D for now (the per-frame amplitude scalar).
+/// When `vec128` lands we extend the inner pass to component-wise L1 across
+/// the embedding dimensions; the outer shape (length-normalise the trailing
+/// window of `recent` against the signature) stays.
+fn signature_score(sig: &Signature, recent: &VecDeque<f64>) -> f32 {
+    if sig.vectors.is_empty() {
+        return 0.0;
+    }
+    let window = sig.vectors.len().min(recent.len());
+    if window == 0 {
+        return 0.0;
+    }
+    let start = recent.len() - window;
+    let mut sum: f64 = 0.0;
+    for (i, sig_vec) in sig.vectors.iter().rev().take(window).enumerate() {
+        let s = sig_vec.first().copied().unwrap_or(0.0);
+        let r = recent.get(recent.len() - 1 - i).copied().unwrap_or(0.0);
+        sum += (s - r).abs();
+    }
+    let mean_abs = sum / window as f64;
+    // Map to (0, 1] — 0 mean-abs error → 1.0, growing error → ~0.
+    let score = 1.0 / (1.0 + mean_abs);
+    let _ = start; // reserved for future windowing changes
+    score as f32
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    fn sig(id: &str, vectors: Vec<f64>, threshold: f32) -> Signature {
+        Signature {
+            id: id.to_string(),
+            label: id.to_string(),
+            vectors: vectors.into_iter().map(|v| vec![v]).collect(),
+            dtw: SignatureDtw {
+                window: 8,
+                step_pattern: "symmetric2".to_string(),
+            },
+            promotion_threshold: threshold,
+        }
+    }
+
+    #[test]
+    fn snapshot_is_unknown_before_first_frame() {
+        let st = IntrospectionState::new();
+        let s = st.snapshot();
+        assert_eq!(s.frame_count, 0);
+        assert_eq!(s.regime, Regime::Unknown);
+        assert!(s.lyapunov_exponent.is_none());
+        assert_eq!(s.attractor_confidence, 0.0);
+        assert!(s.top_k_similarity.is_empty());
+    }
+
+    #[test]
+    fn update_advances_frame_count_and_timestamp() {
+        let mut st = IntrospectionState::new();
+        st.update(1_000, 0.5).unwrap();
+        st.update(2_000, 0.7).unwrap();
+        let s = st.snapshot();
+        assert_eq!(s.frame_count, 2);
+        assert_eq!(s.timestamp_ns, 2_000);
+    }
+
+    #[test]
+    fn empty_library_yields_empty_similarity() {
+        let mut st = IntrospectionState::new();
+        for k in 0..40 {
+            st.update(k * 33_000_000, (k as f64).sin()).unwrap();
+        }
+        assert!(st.snapshot().top_k_similarity.is_empty());
+    }
+
+    #[test]
+    fn single_signature_scores_higher_when_recent_matches() {
+        let lib = SignatureLibrary::from_signatures(vec![sig(
+            "walking_slow",
+            vec![1.0, 2.0, 3.0, 4.0, 5.0],
+            0.5,
+        )]);
+        let cfg = IntrospectionConfig {
+            trajectory_len: 32,
+            embedding_dim: 1,
+            analyze_every_n: 16,
+            library: lib,
+        };
+        let mut st = IntrospectionState::with_config(cfg);
+        // Feed a ramp that ends 1..=5 — close match for the signature.
+        for (i, v) in [1.0f64, 2.0, 3.0, 4.0, 5.0].iter().enumerate() {
+            st.update((i as u64) * 1_000_000, *v).unwrap();
+        }
+        let s = st.snapshot();
+        assert_eq!(s.top_k_similarity.len(), 1);
+        let m = &s.top_k_similarity[0];
+        assert_eq!(m.signature_id, "walking_slow");
+        // Perfect ramp match → score very close to 1.0.
+        assert!(m.score > 0.95, "score = {}", m.score);
+        assert!(m.above_threshold);
+    }
+
+    #[test]
+    fn divergent_signature_scores_low_and_below_threshold() {
+        let lib = SignatureLibrary::from_signatures(vec![sig(
+            "walking_slow",
+            vec![1.0, 2.0, 3.0, 4.0, 5.0],
+            0.5,
+        )]);
+        let cfg = IntrospectionConfig {
+            trajectory_len: 32,
+            embedding_dim: 1,
+            analyze_every_n: 16,
+            library: lib,
+        };
+        let mut st = IntrospectionState::with_config(cfg);
+        for (i, v) in [100.0f64, 200.0, 300.0, 400.0, 500.0].iter().enumerate() {
+            st.update((i as u64) * 1_000_000, *v).unwrap();
+        }
+        let m = &st.snapshot().top_k_similarity[0];
+        assert!(m.score < 0.05, "score = {}", m.score);
+        assert!(!m.above_threshold);
+    }
+
+    #[test]
+    fn top_k_truncates_and_orders_descending() {
+        let lib = SignatureLibrary::from_signatures(vec![
+            sig("a", vec![1.0, 2.0, 3.0], 0.3),
+            sig("b", vec![10.0, 20.0, 30.0], 0.3),
+            sig("c", vec![100.0, 200.0, 300.0], 0.3),
+            sig("d", vec![1.5, 2.5, 3.5], 0.3),
+        ]);
+        let cfg = IntrospectionConfig {
+            trajectory_len: 32,
+            embedding_dim: 1,
+            analyze_every_n: 16,
+            library: lib,
+        };
+        let mut st = IntrospectionState::with_config(cfg);
+        // The trailing 3 values match "a" exactly.
+        for (i, v) in [1.0f64, 2.0, 3.0].iter().enumerate() {
+            st.update((i as u64) * 1_000_000, *v).unwrap();
+        }
+        let top = &st.snapshot().top_k_similarity;
+        // Default DEFAULT_TOP_K = 5; library has 4, so we get 4 back.
+        assert_eq!(top.len(), 4);
+        // Strictly descending by score.
+        for w in top.windows(2) {
+            assert!(w[0].score >= w[1].score, "not descending: {:?}", top);
+        }
+        // First one is "a" (perfect 1..3 match) at score ~1.
+        assert_eq!(top[0].signature_id, "a");
+        assert!(top[0].score > 0.95);
+    }
+
+    #[test]
+    fn signature_with_empty_vectors_does_not_panic() {
+        let lib = SignatureLibrary::from_signatures(vec![sig("empty", vec![], 0.5)]);
+        let mut st = IntrospectionState::with_config(IntrospectionConfig {
+            trajectory_len: 16,
+            embedding_dim: 1,
+            analyze_every_n: 8,
+            library: lib,
+        });
+        st.update(1_000, 1.0).unwrap();
+        let s = st.snapshot();
+        assert_eq!(s.top_k_similarity.len(), 1);
+        assert_eq!(s.top_k_similarity[0].score, 0.0);
+        assert!(!s.top_k_similarity[0].above_threshold);
+    }
+
+    #[test]
+    fn regime_classification_eventually_runs() {
+        // Feed >100 points of a periodic signal — analyzer's
+        // min_points_for_analysis is 100. We don't assert a specific regime
+        // (the classification rules are midstream's, not ours) — only that
+        // the analyze step runs without erroring and a non-Unknown classification
+        // is produced.
+        let mut st = IntrospectionState::with_config(IntrospectionConfig {
+            trajectory_len: 256,
+            embedding_dim: 1,
+            analyze_every_n: 8,
+            library: SignatureLibrary::new(),
+        });
+        for k in 0..200u64 {
+            let v = (k as f64 * 0.1).sin();
+            st.update(k * 33_000_000, v).unwrap();
+        }
+        let s = st.snapshot();
+        // After 200 points + analyze_every_n=8 fires, the analyzer should have
+        // produced a classification at least once.
+        assert!(
+            s.regime != Regime::Unknown || s.lyapunov_exponent.is_some(),
+            "expected regime classified or Lyapunov set after 200 frames; got {:?}",
+            s
+        );
+    }
+}
diff --git a/v2/crates/wifi-densepose-sensing-server/src/lib.rs b/v2/crates/wifi-densepose-sensing-server/src/lib.rs
index 68fa17a9..c9f9445e 100644
--- a/v2/crates/wifi-densepose-sensing-server/src/lib.rs
+++ b/v2/crates/wifi-densepose-sensing-server/src/lib.rs
@@ -4,8 +4,10 @@
 //! - Vital sign detection from WiFi CSI amplitude data
 //! - RVF (RuVector Format) binary container for model weights
 //! - Opt-in bearer-token auth for the `/api/v1/*` HTTP surface (`bearer_auth`)
+//! - Real-time CSI introspection / low-latency tap (`introspection`, ADR-099)
 
 pub mod bearer_auth;
+pub mod introspection;
 pub mod vital_signs;
 pub mod rvf_container;
 pub mod rvf_pipeline;