feat(soul): Stage 1 structural audit as a real route — an annotated characterization, not a score (#91)

`runStructuralAudit` has been an advertised MCP tool with nothing behind it: the
dispatcher GET'd /session/begin and returned that unrelated session digest under
an audit tool's name. Meanwhile the failure the audit would have caught ran
silently for about three weeks — the soul reporting 103,089 nodes while the
engram, which OWNS persistence, held ~79,900, a crash discarding the difference,
and every boot reporting green throughout, because nothing in the system ever
compared the two sides.

WHAT THE PATENT SPECIFIES, AND HOW IT SHAPED THIS
  CGI provisional, 05-detailed-description.md, "Stage 1: Structural audit 430".
  Two clauses did the design work. First the four things the module evaluates:
  the density and typed distribution of causal edges; value/execution-record
  consistency; the richness and connectivity of the self-model; and wonder-
  manifest authenticity. Second, and decisively: it "produces a coherence
  assessment 432 — NOT A BINARY SCORE but an annotated characterization of the
  graph's structural properties."

  So every finding carries its numbers AND a plain-language note saying what
  they mean and how they were obtained. There is no pass/fail and no composite
  health figure, and `"score":null` is emitted explicitly so a reader cannot
  mistake its absence for an omission.

WHAT IS IN STAGE 1 (four findings)
  owner_runtime_divergence   — the motivating case. Runtime counts vs the owner's
      own GET /api/stats, the delta, and the trend against the previous audit, so
      a second call answers "is the gap growing?" rather than restating it.
  self_model_connectivity    — the three identity pillars plus the self root:
      present, content length, one-hop degree. This RETIRES the Claude-side vitals
      identity block, which lived outside the system it was checking and went on
      reporting green while the memory-philosophy pillar was absent from the live
      graph. Asking the running soul is the designed mechanism; a shell probe was
      the fourth patch on the same hole.
  typed_edge_distribution    — exact counts against the claim-10 vocabulary, plus
      density, plus a separate count of LOWERCASE near-misses ("causes" vs
      "Causes"): "the vocabulary is unused" and "the vocabulary is misspelled by
      the write paths" are different defects with different fixes.
  orphans_and_dangling_edges — the tool's own long-standing promise.

WHAT IS DEFERRED, AND WHY IT IS DATA RATHER THAN A COMMENT
  Value/execution-record consistency and wonder-manifest authenticity ship as a
  `deferred` array that MEASURES the populations they would need (Prediction and
  WonderQuestion nodes) and reports those counts as the reason. Both are ~0 today
  — WonderQuestion because of a known write/read node-type mismatch. Asserting
  value coherence or a pull-weight correlation on an empty population would be a
  fabricated result, which is worse than a stated gap.

MEASUREMENT HONESTY: EXACT WHERE CHEAP, SAMPLED WHERE NOT, ALWAYS LABELLED
  Counts, edge typing and self-model connectivity are exact. Orphan and dangling
  rates are sampled, because engram_find_node_index is a linear scan — an
  exhaustive dangling check is O(nodes x edges), ~2.2e9 string compares at today's
  scale. Samples are UNIFORM across the whole population (str_index_of_all gives
  every edge offset in one pass, so any index is O(1); json_array_get would have
  been O(n^2)), never head-of-list, and each figure ships with its own sampled /
  population / exhaustive fields. ?edge_sample= and ?node_sample= at population
  size run either check exhaustively. The real fix is an id index in the runtime.

ONE BUG THIS FOUND IN ITSELF, CAUGHT IN TEST
  http_get does not return "" when the owner is unreachable — it returns a JSON
  error object. Testing only for "" made a DEAD owner read as reachable with
  node_count 0, so the audit reported 100% divergence and named it data loss.
  Reachability is now proved by the presence of the node_count field, and the
  owner's raw reply is attached. A confident wrong answer is exactly what this
  route exists to stop.

  Edge findings need relation labels and the runtime has no edge-enumeration
  builtin, so they use the same scratch export GET /api/graph/edges already uses
  (engram_save to TMPDIR, never the owner's canonical file — #117). That is a
  large write on a large graph, so this is a manual route, not a timer; ?edges=0
  skips it.

  neuron-api.el:900-1273  handler + helpers
  routes.el:567,752       GET and POST /api/neuron/audit/structural
  mcp-wrapper/src/main.el:113,682  tool description + dispatch off /session/begin
  dist/soul.c             regenerated (1255 bodies)

Rung: E2E-VERIFIED. Soul built from this branch (gen-soul-amalgam + cc-brain,
921,192 bytes, 16 warnings, 0 errors), booted on throwaway ports 7893/7896/7897
with throwaway HOMEs against a stub owner on 7894. Three scenarios pass: owner
reachable (runtime 62 vs owner 42, delta 20 / 32.2%, trend flat on the second
call; 12/20 edges claim-10 typed, 3 lowercase near-misses; 50/62 orphans, 3/20
dangling — every figure matches the fixture by construction), owner unreachable
(reported as a finding with the raw reply, not a crash), and file mode (owner
"none", divergence undefined). Reached end-to-end through the MCP tool via a
locally built wrapper. verify-soul-contract.sh: GATE PASS, 27/27 routes +
immutability. No process left running; live :7770 and :8742 untouched (GET only).

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>

neuron-api.el

@@ -889,3 +889,462 @@ fn handle_api_consolidate(body: String) -> String {
     }
     return "{\"ok\":true,\"snapshot\":\"" + snap + "\"}"
 }
+
+// ── Stage 1: structural audit ─────────────────────────────────────────────────
+//
+// WHAT THIS IMPLEMENTS
+//   The CGI provisional, 05-detailed-description.md, "Stage 1: Structural audit
+//   430". Verbatim, the audit module evaluates: the density and typed
+//   distribution of causal edges; the consistency between value nodes and
+//   execution-record neighborhoods; the richness and connectivity of the
+//   self-model; and the authenticity of open-question nodes in the wonder
+//   manifest. It "produces a coherence assessment 432 — NOT A BINARY SCORE but
+//   an annotated characterization of the graph's structural properties".
+//
+//   That last clause is the whole shape of this handler. Every finding carries
+//   its own numbers AND a plain-language note saying what the numbers mean and
+//   how they were obtained. There is no pass/fail, no percentage-of-health, no
+//   composite score, and `"score":null` is emitted explicitly so a downstream
+//   reader cannot mistake its absence for an omission.
+//
+// WHY IT EXISTS NOW, AND WHY THE FIRST FINDING IS THE ONE IT IS
+//   `runStructuralAudit` has been an advertised MCP tool with nothing behind it:
+//   the dispatcher GET'd /session/begin and returned that blob (mcp-wrapper/src/
+//   main.el). Meanwhile the failure the audit would have caught ran silently for
+//   about three weeks — the soul reported 103,089 nodes while the engram, which
+//   OWNS persistence, held ~79,900; a crash discarded the difference. Every boot
+//   reported green throughout, because nothing in the system ever compared the
+//   two sides. So finding 1 is owner-versus-runtime divergence: it is the check
+//   whose absence cost real memory, and it is cheap and exact.
+//
+// WHAT IS DELIBERATELY NOT HERE (stage 1b, see the `deferred` array in the
+// response): value/execution-record consistency and wonder-manifest
+// authenticity. Both need node types that barely exist in this graph today —
+// the response MEASURES those populations and reports the counts as the reason,
+// rather than asserting a deferral without evidence.
+//
+// MEASUREMENT HONESTY: EXACT WHERE CHEAP, SAMPLED WHERE NOT, ALWAYS LABELLED
+//   Counts, edge typing and self-model connectivity are exact. Orphan rate and
+//   dangling-edge rate are SAMPLED, because the engram runtime has no node-id
+//   index — `engram_find_node_index` is a linear scan over every node, so an
+//   exhaustive dangling check is O(nodes x edges) (~2.2e9 string compares at
+//   today's scale, tens of seconds inside one request). The samples are UNIFORM
+//   across the whole population, not head-of-list, and every sampled figure is
+//   emitted with its own `sampled` / `population` fields plus an extrapolation
+//   labelled as such. Raise `?edge_sample=` / `?node_sample=` to the population
+//   size to run either check exhaustively and pay the time. The real fix is an
+//   id index in the runtime; that is the engram repo's, not this handler's.
+
+// audit_pct1 — one-decimal percentage as a bare JSON number, sign-safe.
+// Integer math only: EL has no fixed-precision formatter, and float_to_str
+// would put an unbounded mantissa in the response.
+fn audit_pct1(num: Int, den: Int) -> String {
+    if den <= 0 { return "null" }
+    let neg: Bool = num < 0
+    let a: Int = if neg { 0 - num } else { num }
+    let tenths: Int = (a * 1000) / den
+    let whole: Int = tenths / 10
+    let frac: Int = tenths - (whole * 10)
+    let sign: String = if neg { "-" } else { "" }
+    return sign + int_to_str(whole) + "." + int_to_str(frac)
+}
+
+// audit_finding — the one envelope every finding uses: name, the measurements,
+// and the annotation. Keeping it in one place is what stops the characterization
+// from degenerating into a bag of numbers with no reading attached.
+fn audit_finding(name: String, measured: String, note: String) -> String {
+    return "{\"finding\":\"" + name + "\""
+        + ",\"measured\":{" + measured + "}"
+        + ",\"note\":\"" + api_json_escape(note) + "\"}"
+}
+
+// audit_str_at — read the quoted string value starting at byte `start`.
+// Slices a bounded window rather than the tail of the (multi-MB) edges array, so
+// this is O(window) per call instead of O(remaining input).
+fn audit_str_at(s: String, start: Int, maxlen: Int) -> String {
+    let n: Int = str_len(s)
+    if start < 0 || start >= n { return "" }
+    let end_guess: Int = start + maxlen
+    let stop: Int = if end_guess > n { n } else { end_guess }
+    let win: String = str_slice(s, start, stop)
+    let q: Int = str_index_of(win, "\"")
+    if q < 0 { return "" }
+    return str_slice(win, 0, q)
+}
+
+// audit_rel_count — exact count of edges carrying `rel`, by scanning the emitted
+// edge array for the literal `"relation":"<rel>"`. engram_emit_edge_json writes
+// metadata ESCAPED as a string, so no nested object can contain that literal and
+// the count cannot be inflated by edge payloads.
+fn audit_rel_count(edges: String, rel: String) -> Int {
+    return str_count(edges, "\"relation\":\"" + rel + "\"")
+}
+
+// audit_owner_stats — ask the persistence OWNER for its own counts.
+// Returns "" when there is no HTTP owner configured or the owner is unreachable;
+// both are reported as findings, never as a failure of the audit.
+fn audit_owner_stats(url: String) -> String {
+    if str_eq(url, "") { return "" }
+    return http_get(url + "/api/stats")
+}
+
+// audit_divergence — FINDING 1. Runtime (this soul's in-process graph) versus
+// the persistence owner's own count. Trend is measured against the previous
+// audit recorded in soul state, so a second call answers "is the gap growing?"
+// rather than just restating it.
+fn audit_divergence() -> String {
+    let rt_nodes: Int = engram_node_count()
+    let rt_edges: Int = engram_edge_count()
+    let url: String = wt_engram_url()
+
+    if str_eq(url, "") {
+        return audit_finding("owner_runtime_divergence",
+            "\"runtime_nodes\":" + int_to_str(rt_nodes)
+            + ",\"runtime_edges\":" + int_to_str(rt_edges)
+            + ",\"owner\":\"none\",\"owner_reachable\":false",
+            "No HTTP persistence owner is configured, so this soul IS the owner "
+            + "(file mode) and divergence is not defined. This check only has "
+            + "meaning when ENGRAM_URL points at a separate engram that owns the "
+            + "canonical store.")
+    }
+
+    let stats: String = audit_owner_stats(url)
+    // REACHABILITY IS PROVED BY THE PAYLOAD, NOT BY A NON-EMPTY REPLY.
+    // http_get does not return "" on a connection failure — it returns a JSON
+    // error object ({"error":"Failed to connect to ... Couldn't connect to
+    // server"}). Testing only for "" made a DEAD owner read as reachable with
+    // node_count 0, i.e. the audit would have reported a 100% divergence and
+    // named it as data loss. That false positive is worse than no check at all:
+    // it is precisely the kind of confident wrong answer this route exists to
+    // stop. Require the field the contract promises.
+    let owner_nc_raw: String = json_get_raw(stats, "node_count")
+    if str_eq(stats, "") || str_eq(owner_nc_raw, "") {
+        return audit_finding("owner_runtime_divergence",
+            "\"runtime_nodes\":" + int_to_str(rt_nodes)
+            + ",\"runtime_edges\":" + int_to_str(rt_edges)
+            + ",\"owner\":\"" + api_json_escape(url) + "\",\"owner_reachable\":false"
+            + ",\"owner_reply\":\"" + api_json_escape(api_utf8_trunc(stats, 200)) + "\"",
+            "The persistence owner at " + url + " did not return a node_count "
+            + "from GET /api/stats. Divergence is UNKNOWN, NOT ZERO — an owner "
+            + "that cannot be read is exactly the condition under which the "
+            + "runtime's own count means least, and reporting 0 for the owner "
+            + "would manufacture a total-loss reading out of a network error. "
+            + "Reported as a finding rather than raised as an error so the rest "
+            + "of the audit still returns; the owner's raw reply is in "
+            + "owner_reply.")
+    }
+
+    let ow_nodes: Int = json_get_int(stats, "node_count")
+    let ow_edges: Int = json_get_int(stats, "edge_count")
+    let d_nodes: Int = rt_nodes - ow_nodes
+    let d_edges: Int = rt_edges - ow_edges
+
+    // Trend against the previous audit in this soul's state.
+    let prev_raw: String = state_get("audit_prev_node_delta")
+    let prev: Int = str_to_int(prev_raw)
+    let abs_now: Int = if d_nodes < 0 { 0 - d_nodes } else { d_nodes }
+    let abs_prev: Int = if prev < 0 { 0 - prev } else { prev }
+    let trend: String = if str_eq(prev_raw, "") {
+        "no_prior_audit"
+    } else {
+        if abs_now > abs_prev { "growing" } else {
+            if abs_now < abs_prev { "shrinking" } else { "flat" }
+        }
+    }
+    state_set("audit_prev_node_delta", int_to_str(d_nodes))
+    state_set("audit_prev_ts", int_to_str(time_now()))
+
+    let note_head: String = if d_nodes == 0 {
+        "Runtime and owner agree on node count."
+    } else {
+        "Runtime holds " + int_to_str(d_nodes) + " nodes (" + audit_pct1(d_nodes, rt_nodes)
+        + "% of its own graph) that the persistence owner does not report. Nodes "
+        + "that exist only in runtime memory do not survive a restart."
+    }
+    return audit_finding("owner_runtime_divergence",
+        "\"runtime_nodes\":" + int_to_str(rt_nodes)
+        + ",\"runtime_edges\":" + int_to_str(rt_edges)
+        + ",\"owner\":\"" + api_json_escape(url) + "\",\"owner_reachable\":true"
+        + ",\"owner_nodes\":" + int_to_str(ow_nodes)
+        + ",\"owner_edges\":" + int_to_str(ow_edges)
+        + ",\"node_delta\":" + int_to_str(d_nodes)
+        + ",\"edge_delta\":" + int_to_str(d_edges)
+        + ",\"node_delta_pct_of_runtime\":" + audit_pct1(d_nodes, rt_nodes)
+        + ",\"trend_vs_previous_audit\":\"" + trend + "\""
+        + ",\"previous_node_delta\":" + (if str_eq(prev_raw, "") { "null" } else { int_to_str(prev) }),
+        note_head + " Trend against the previous audit recorded in this soul's "
+        + "state: " + trend + ". This is the comparison whose absence let a "
+        + "~24,000-node loss run for weeks with every boot reporting green.")
+}
+
+// audit_edge_typing — FINDING 2. Density plus the typed distribution the patent
+// asks for, against the claim-10 relation vocabulary. Exact: str_count over the
+// emitted edge array, one linear pass per relation.
+fn audit_edge_typing(edges: String, total_edges: Int, node_total: Int) -> String {
+    let c_sup: Int = audit_rel_count(edges, "Supersedes")
+    let c_cau: Int = audit_rel_count(edges, "Causes")
+    let c_con: Int = audit_rel_count(edges, "Contains")
+    let c_ref: Int = audit_rel_count(edges, "References")
+    let c_ctr: Int = audit_rel_count(edges, "Contradicts")
+    let c_exe: Int = audit_rel_count(edges, "Exemplifies")
+    let c_act: Int = audit_rel_count(edges, "Activates")
+    let c_tmp: Int = audit_rel_count(edges, "TemporallyPrecedes")
+    let typed: Int = c_sup + c_cau + c_con + c_ref + c_ctr + c_exe + c_act + c_tmp
+
+    // Lowercase near-misses: the same eight concepts written by the ad-hoc write
+    // paths (linkEntities defaults to "associates", linkCausal to "causes").
+    // Counted separately because "the vocabulary is unused" and "the vocabulary
+    // is used in the wrong case" are different defects with different fixes.
+    let l_sup: Int = audit_rel_count(edges, "supersedes")
+    let l_cau: Int = audit_rel_count(edges, "causes")
+    let l_con: Int = audit_rel_count(edges, "contains")
+    let l_ref: Int = audit_rel_count(edges, "references")
+    let l_ctr: Int = audit_rel_count(edges, "contradicts")
+    let l_exe: Int = audit_rel_count(edges, "exemplifies")
+    let l_act: Int = audit_rel_count(edges, "activates")
+    let l_tmp: Int = audit_rel_count(edges, "temporallyPrecedes")
+    let near: Int = l_sup + l_cau + l_con + l_ref + l_ctr + l_exe + l_act + l_tmp
+
+    let untyped: Int = total_edges - typed
+    return audit_finding("typed_edge_distribution",
+        "\"total_edges\":" + int_to_str(total_edges)
+        + ",\"total_nodes\":" + int_to_str(node_total)
+        // Density per 100 nodes, not per node: EL has no fixed-precision float
+        // formatter, and "0.3 edges per node" rounded to an integer is a lie.
+        + ",\"edges_per_100_nodes\":" + audit_pct1(total_edges, node_total)
+        + ",\"claim10_typed\":" + int_to_str(typed)
+        + ",\"claim10_typed_pct\":" + audit_pct1(typed, total_edges)
+        + ",\"outside_claim10_vocabulary\":" + int_to_str(untyped)
+        + ",\"lowercase_near_miss\":" + int_to_str(near)
+        + ",\"by_relation\":{"
+        + "\"Supersedes\":" + int_to_str(c_sup)
+        + ",\"Causes\":" + int_to_str(c_cau)
+        + ",\"Contains\":" + int_to_str(c_con)
+        + ",\"References\":" + int_to_str(c_ref)
+        + ",\"Contradicts\":" + int_to_str(c_ctr)
+        + ",\"Exemplifies\":" + int_to_str(c_exe)
+        + ",\"Activates\":" + int_to_str(c_act)
+        + ",\"TemporallyPrecedes\":" + int_to_str(c_tmp) + "}",
+        "Only " + int_to_str(typed) + " of " + int_to_str(total_edges)
+        + " edges use the claim-10 causal vocabulary; the remainder are ad-hoc "
+        + "relation strings, which is why the graph's causal claims cannot yet "
+        + "be checked for internal consistency — an untyped edge asserts "
+        + "association, not causation. " + int_to_str(near) + " edges use a "
+        + "lowercase spelling of a claim-10 relation: those are near-misses the "
+        + "write paths could be corrected to emit, not genuinely foreign types.")
+}
+
+// audit_orphans_dangling — FINDING 3. Both figures are SAMPLED; see the header
+// for why exhaustive is O(nodes x edges) on this runtime.
+//
+// An "orphan" here is a node with zero RESOLVABLE edges: engram_neighbors_json
+// drops any edge whose other endpoint does not resolve to a node, so a node
+// whose only edges are dangling reads as an orphan. That is the right reading —
+// such a node is unreachable by traversal — but it is stated rather than hidden.
+fn audit_orphans_dangling(edges: String, total_edges: Int, node_total: Int,
+                          edge_cap: Int, node_cap: Int) -> String {
+    // ── orphan sample: uniform stride over the node store ──
+    let n_take: Int = if node_total < node_cap { node_total } else { node_cap }
+    let n_stride: Int = if n_take > 0 { node_total / n_take } else { 1 }
+    let n_stride = if n_stride < 1 { 1 } else { n_stride }
+    let orphans: Int = 0
+    let n_checked: Int = 0
+    let j: Int = 0
+    while j < n_take {
+        let one: String = engram_scan_nodes_json(1, j * n_stride)
+        let nid: String = json_get(json_array_get(one, 0), "id")
+        if !str_eq(nid, "") {
+            let nbrs: String = engram_neighbors_json(nid, 1, "both")
+            let deg: Int = json_array_len(nbrs)
+            let orphans = if deg == 0 { orphans + 1 } else { orphans }
+            let n_checked = n_checked + 1
+        }
+        let j = j + 1
+    }
+
+    // ── dangling sample: uniform stride over the edge array ──
+    // str_index_of_all gives every edge's field offsets in ONE linear pass, so
+    // any index can be read in O(1). json_array_get would have been O(i) per
+    // element and O(n^2) over the array.
+    let from_pos: [Int] = str_index_of_all(edges, "\"from_id\":\"")
+    let to_pos: [Int] = str_index_of_all(edges, "\"to_id\":\"")
+    let nf: Int = len(from_pos)
+    let nt: Int = len(to_pos)
+    let ne: Int = if nf < nt { nf } else { nt }
+    let e_take: Int = if ne < edge_cap { ne } else { edge_cap }
+    let e_stride: Int = if e_take > 0 { ne / e_take } else { 1 }
+    let e_stride = if e_stride < 1 { 1 } else { e_stride }
+    let dangling: Int = 0
+    let e_checked: Int = 0
+    let i: Int = 0
+    while i < ne && e_checked < e_take {
+        let fid: String = audit_str_at(edges, get(from_pos, i) + 11, 96)
+        let tid: String = audit_str_at(edges, get(to_pos, i) + 9, 96)
+        let f_gone: Bool = str_eq(engram_get_node_json(fid), "{}")
+        let t_gone: Bool = if f_gone { true } else { str_eq(engram_get_node_json(tid), "{}") }
+        let dangling = if f_gone || t_gone { dangling + 1 } else { dangling }
+        let e_checked = e_checked + 1
+        let i = i + e_stride
+    }
+
+    let orphan_est: Int = if n_checked > 0 { (orphans * node_total) / n_checked } else { 0 }
+    let dangle_est: Int = if e_checked > 0 { (dangling * total_edges) / e_checked } else { 0 }
+    let exhaustive_n: String = if n_checked >= node_total { "true" } else { "false" }
+    let exhaustive_e: String = if e_checked >= ne { "true" } else { "false" }
+
+    return audit_finding("orphans_and_dangling_edges",
+        "\"nodes_population\":" + int_to_str(node_total)
+        + ",\"nodes_sampled\":" + int_to_str(n_checked)
+        + ",\"nodes_sample_exhaustive\":" + exhaustive_n
+        + ",\"orphans_in_sample\":" + int_to_str(orphans)
+        + ",\"orphan_rate_pct\":" + audit_pct1(orphans, n_checked)
+        + ",\"orphans_extrapolated\":" + int_to_str(orphan_est)
+        + ",\"edges_population\":" + int_to_str(total_edges)
+        + ",\"edges_sampled\":" + int_to_str(e_checked)
+        + ",\"edges_sample_exhaustive\":" + exhaustive_e
+        + ",\"dangling_in_sample\":" + int_to_str(dangling)
+        + ",\"dangling_rate_pct\":" + audit_pct1(dangling, e_checked)
+        + ",\"dangling_extrapolated\":" + int_to_str(dangle_est),
+        "Orphan = zero RESOLVABLE edges, so a node whose only edges dangle counts "
+        + "as an orphan; either way it is unreachable by traversal. Dangling = an "
+        + "edge with an endpoint id that resolves to no node. Both are uniform "
+        + "stride samples over the whole population, not the head of the list; "
+        + "the extrapolations are estimates and are labelled as such. Pass "
+        + "?node_sample= / ?edge_sample= at or above the population size to run "
+        + "either check exhaustively. A high orphan rate is a characterization, "
+        + "not a verdict: an accumulating store legitimately holds unlinked "
+        + "material. It becomes a defect when the write paths were SUPPOSED to "
+        + "link and did not.")
+}
+
+// audit_pillar — one self-model pillar: present, how much content, how connected.
+fn audit_pillar(key: String, id: String) -> String {
+    let node: String = engram_get_node_json(id)
+    let present: Bool = !str_eq(node, "{}") && !str_eq(node, "")
+    if !present {
+        return "\"" + key + "\":{\"id\":\"" + id + "\",\"present\":false"
+            + ",\"content_length\":0,\"degree\":0}"
+    }
+    let content: String = json_get(node, "content")
+    let deg: Int = json_array_len(engram_neighbors_json(id, 1, "both"))
+    return "\"" + key + "\":{\"id\":\"" + id + "\",\"present\":true"
+        + ",\"label\":\"" + api_json_escape(json_get(node, "label")) + "\""
+        + ",\"tier\":\"" + api_json_escape(json_get(node, "tier")) + "\""
+        + ",\"content_length\":" + int_to_str(str_len(content))
+        + ",\"degree\":" + int_to_str(deg) + "}"
+}
+
+// audit_self_model — FINDING 4. "the richness and connectivity of the
+// self-model ... is it connected to behavioral evidence?"
+//
+// This finding RETIRES the Claude-side vitals identity block. That check lived
+// outside the system it was checking — a shell script grepping a snapshot — so
+// it could only ever report on a file, and it went on reporting green while the
+// memory-philosophy pillar was absent from the live graph for about three weeks.
+// Asking the running soul about its own three pillars is the designed mechanism;
+// a shell probe was the fourth patch on the same hole.
+fn audit_self_model() -> String {
+    let dna: String = audit_pillar("intellectual_dna", "kn-5adecd7e-d6db-4576-87fe-6ef8a935cea6")
+    let val: String = audit_pillar("values_hub", "kn-5b606390-a52d-4ca2-8e0e-eba141d13440")
+    let phi: String = audit_pillar("memory_philosophy", "kn-dcfe04b3-3702-4cac-b6f0-ecb4db837eee")
+    let root: String = audit_pillar("self_root", "kn-efeb4a5b-5aff-4759-8a97-7233099be6ee")
+    return audit_finding("self_model_connectivity",
+        "\"pillars\":{" + dna + "," + val + "," + phi + "," + root + "}",
+        "The three identity pillars plus the self root. `degree` counts nodes "
+        + "reachable in one hop in either direction — the self-model's connection "
+        + "to the rest of the graph. present:false on any pillar is the condition "
+        + "that ran undetected for weeks; content_length distinguishes a pillar "
+        + "that is present from one that is present but hollowed out. The patent "
+        + "also asks whether the self-model makes ACCURATE PREDICTIONS about the "
+        + "system's own behavior; that half needs Prediction nodes and is deferred "
+        + "with the rest of stage 1b below.")
+}
+
+// audit_deferred — what stage 1 does NOT yet evaluate, with the measured reason.
+// Emitted as data, not as a comment, so a reader of the assessment sees the gap
+// and its evidence rather than inferring completeness from silence.
+fn audit_deferred() -> String {
+    let preds: Int = json_array_len(api_or_empty(engram_scan_nodes_by_type_json("Prediction", 50, 0)))
+    let wonders: Int = json_array_len(api_or_empty(engram_scan_nodes_by_type_json("WonderQuestion", 50, 0)))
+    return "[{\"deferred\":\"value_execution_record_consistency\""
+        + ",\"stage\":\"1b\""
+        + ",\"measured\":{\"prediction_nodes_found\":" + int_to_str(preds) + "}"
+        + ",\"reason\":\"" + api_json_escape(
+            "The patent asks whether the execution history SUPPORTS the stated "
+            + "values or shows systematic conflict. That requires execution "
+            + "records tied to value nodes and predictions to score them against. "
+            + "Prediction nodes found (capped at 50): " + int_to_str(preds)
+            + ". Asserting value/execution coherence on that population would be "
+            + "a fabricated result, which is worse than a stated gap.") + "\"}"
+        + ",{\"deferred\":\"wonder_manifest_authenticity\""
+        + ",\"stage\":\"1b\""
+        + ",\"measured\":{\"wonder_question_nodes_found\":" + int_to_str(wonders) + "}"
+        + ",\"reason\":\"" + api_json_escape(
+            "The patent asks whether pull weights CORRELATE WITH GENUINE "
+            + "PREDICTION UNCERTAINTY or are uniform/externally assigned — a "
+            + "correlation between two populations. WonderQuestion nodes readable "
+            + "by type (capped at 50): " + int_to_str(wonders) + ", against "
+            + int_to_str(preds) + " Prediction nodes. There is a known write/read "
+            + "node-type mismatch on the wonder path; until that is fixed and both "
+            + "populations exist, any correlation reported here would be noise.") + "\"}]"
+}
+
+// handle_api_structural_audit — Stage 1. Returns the coherence assessment 432:
+// an annotated characterization, explicitly NOT a score.
+//
+// COST NOTE: the edge findings need the relation labels, and the runtime exposes
+// no edge-enumeration builtin. The only way to see them is the same one
+// GET /api/graph/edges already uses — engram_save to a SCRATCH path (never the
+// owner's canonical file; see routes.el, neuron#117) and read the array back.
+// On a large graph that is a multi-hundred-MB write, so this is a manual audit
+// route, not something to put on a timer. Pass ?edges=0 to skip both edge
+// findings and get the divergence + self-model readings cheaply.
+fn handle_api_structural_audit(method: String, path: String, body: String) -> String {
+    let node_total: Int = engram_node_count()
+    let edge_total: Int = engram_edge_count()
+    let want_edges: Bool = !str_eq(api_query_param(path, "edges"), "0")
+    let edge_cap: Int = api_query_int(path, "edge_sample", 3000)
+    let node_cap: Int = api_query_int(path, "node_sample", 300)
+
+    let divergence: String = audit_divergence()
+    let self_model: String = audit_self_model()
+
+    let edge_part: String = if want_edges {
+        // Scratch export only. state_get("soul_snapshot_path") is deliberately
+        // NOT used: in HTTP-engram mode the soul is not the persistence owner and
+        // must never write the canonical file, not even on a read path.
+        let scratch_dir: String = env("TMPDIR")
+        let scratch_base: String = if str_eq(scratch_dir, "") { "/tmp" } else { scratch_dir }
+        let snap_path: String = scratch_base + "/soul-audit-export-" + state_get("soul_cgi_id") + ".json"
+        // engram_save returns Int (1 ok / 0 fail); str_eq on it SIGSEGVs (#150).
+        let saved: Int = engram_save(snap_path)
+        if saved == 0 {
+            "," + audit_finding("typed_edge_distribution", "\"available\":false",
+                "Could not export the graph to " + snap_path + " for edge analysis, "
+                + "so edge typing and the dangling-edge sample were not run. "
+                + "Reported as a gap, not as zero findings.")
+        } else {
+            // wt_read, not fs_read: fs_read leaves a thread-local length hint that
+            // the NEXT HTTP response would use as its Content-Length, appending
+            // adjacent heap bytes to the reply (see persist.el wt_read).
+            let snap: String = wt_read(snap_path)
+            let edges_raw: String = json_get_raw(snap, "edges")
+            let edges: String = if str_eq(edges_raw, "") { "[]" } else { edges_raw }
+            "," + audit_edge_typing(edges, edge_total, node_total)
+            + "," + audit_orphans_dangling(edges, edge_total, node_total, edge_cap, node_cap)
+        }
+    } else {
+        ""
+    }
+
+    return "{\"audit\":\"structural\",\"stage\":1"
+        + ",\"spec\":\"CGI provisional 05-detailed-description.md, Stage 1: Structural audit 430\""
+        + ",\"assessment\":\"coherence_assessment_432\""
+        + ",\"assessment_kind\":\"annotated_characterization\""
+        + ",\"score\":null"
+        + ",\"score_note\":\"By design. The specification calls for an annotated characterization of the graph's structural properties, not a binary score. Read the findings.\""
+        + ",\"cgi_id\":\"" + api_json_escape(state_get("soul_cgi_id")) + "\""
+        + ",\"ts_ms\":" + int_to_str(time_now())
+        + ",\"findings\":[" + divergence + "," + self_model + edge_part + "]"
+        + ",\"deferred\":" + audit_deferred() + "}"
+}