Merge pull request 'elp: native audio/image efferent surfaces + projector proof-of-shape' (#111) from worktree-agent-aaf04b0a9714c4070 into dev

elp/src/audio-demo.el

@@ -0,0 +1,73 @@
+// audio-demo.el - Drive the native audio surface: render a tone per instrument
+// from its LEARNED signature, then render a small meaning-phrase "piece".
+// Entry point: top-level statement calls main() (same convention as the
+// examples' top-level println(run_test())).
+
+fn micros_to_str(xs: [Int]) -> String {
+    let n: Int = native_list_len(xs)
+    let out: String = ""
+    let i: Int = 0
+    while i < n {
+        if i > 0 { let out: String = out + "," }
+        let out: String = out + int_to_str(native_list_get(xs, i))
+        let i: Int = i + 1
+    }
+    return out
+}
+
+// Render a 1.0s A4 (midi 69) tone from a signature file, print the parsed
+// partials (proving the numbers came from the engram .sig), write the WAV.
+fn render_tone(name: String, sigpath: String, outpath: String, table: [Int]) -> Int {
+    let lines: [String] = sig_load(sigpath)
+    let partials: [Int] = parse_micros(sig_field(lines, "partials"))
+    println("[" + name + "] partials_n=" + sig_field(lines, "partials_n") + "  parsed_partials_micro(scale 1e6)=" + micros_to_str(partials))
+    println("[" + name + "] raw partials line from .sig = " + sig_field(lines, "partials"))
+    let freq: Int = freq_of_midi(69)
+    let note: [Int] = synth_from_sig(lines, freq, 1000, 900, 44100, table)
+    let n: Int = native_list_len(note)
+    let ok: Int = wav_write(outpath, note, n, 44100)
+    println("[" + name + "] rendered " + int_to_str(n) + " samples -> " + outpath + " (write_ok=" + int_to_str(ok) + ")")
+    return n
+}
+
+fn run_demo() -> Int {
+    let table: [Int] = sin_table()
+    fs_mkdir("/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/out")
+
+    println("=== TONES: render A4 (midi 69) from each learned signature ===")
+    render_tone("flute",    "/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/sig/flute.sig",    "/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/out/tone-flute.wav", table)
+    render_tone("clarinet", "/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/sig/clarinet.sig", "/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/out/tone-clarinet.wav", table)
+    render_tone("violin",   "/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/sig/violin.sig",   "/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/out/tone-violin.wav", table)
+    render_tone("piano",    "/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/sig/piano.sig",    "/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/out/tone-piano.wav", table)
+    render_tone("organ",    "/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/sig/organ.sig",    "/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/out/tone-organ.wav", table)
+
+    println("")
+    println("=== PIECE: a 6-frame meaning phrase (incl. a NEG frame) ===")
+    let frames: [[String]] = native_list_empty()
+    let frames: [[String]] = native_list_append(frames, audio_frame("agent",    "aff", "0.9", "0.8", "0", "s1"))
+    let frames: [[String]] = native_list_append(frames, audio_frame("theme",    "aff", "0.7", "0.6", "0", "s2"))
+    let frames: [[String]] = native_list_append(frames, audio_frame("cause",    "aff", "0.8", "0.9", "1", "s3"))
+    let frames: [[String]] = native_list_append(frames, audio_frame("negation", "neg", "0.85", "0.7", "0", "s4"))
+    let frames: [[String]] = native_list_append(frames, audio_frame("goal",     "aff", "0.6", "0.5", "1", "s5"))
+    let frames: [[String]] = native_list_append(frames, audio_frame("result",   "aff", "0.95", "1.0", "0", "s6"))
+
+    // Print the plan so the NEG frame's minor third (+3) vs major (+4) is visible.
+    let nf: Int = native_list_len(frames)
+    let fi: Int = 0
+    while fi < nf {
+        let frame: [String] = native_list_get(frames, fi)
+        let plan: [Int] = plan_note(frame)
+        let pol: String = surface_get(frame, "polarity")
+        let third_name: String = "major(+4)"
+        if str_eq(pol, "neg") { let third_name: String = "MINOR(+3)" }
+        println("frame " + int_to_str(fi) + " relation=" + surface_get(frame, "relation") + " polarity=" + pol + " -> midi=" + int_to_str(native_list_get(plan, 0)) + " dur_ms=" + int_to_str(native_list_get(plan, 1)) + " amp_pm=" + int_to_str(native_list_get(plan, 2)) + " third=" + third_name)
+        let fi: Int = fi + 1
+    }
+
+    let piano_lines: [String] = sig_load("/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/sig/piano.sig")
+    let total: Int = realize_audio(frames, piano_lines, "/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/out/piece.wav", 44100, table)
+    println("PIECE rendered " + int_to_str(total) + " samples -> /Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/out/piece.wav")
+    return total
+}
+
+println("audio-demo main returned samples=" + int_to_str(run_demo()))

elp/src/audio-surface.el

@@ -0,0 +1,400 @@
+// audio-surface.el - Native own-core additive-synthesis audio surface.
+//
+// The AUDIO efferent seam, native, no Python and no library. This renders real
+// PCM .wav bytes from instrument SIGNATURES read from engram-sourced .sig data
+// files (elp/faculty/sig/*.sig) - the partial amplitudes are NEVER literals in
+// this source; they are parsed from the learned signature at run time. That is
+// the whole proof: render-from-learned-signatures.
+//
+// EL has no float arithmetic operator (codegen emits raw int64 ops for + - * /
+// on the shared 64-bit slot) and no float-arithmetic natives - so ALL synthesis
+// math here is own-core INTEGER fixed-point. Angles use a quarter-wave sine
+// table (scale 10000) from a fixed-point Taylor series; amplitudes are parsed to
+// micro (scale 1e6) straight from the .sig text; frequencies are milliHz ints.
+//
+// Pipeline mirrors the two-stage projector (midi.py): plan_note(frame) reads a
+// frame's meaning-geometry slot-map and derives (pitch, duration, amplitude);
+// realize_audio SUPERPOSES the signature's partials (the compose op) and
+// serialises RIFF/WAVE. Same frame -> midi OR audio.
+
+// -- integer decimal + string helpers -----------------------------------------
+
+fn str_to_int_el(s: String) -> Int {
+    let n: Int = str_len(s)
+    let i: Int = 0
+    let v: Int = 0
+    let neg: Bool = false
+    while i < n {
+        let c: Int = str_char_code(s, i)
+        if c == 45 { let neg: Bool = true }
+        if c >= 48 {
+            if c < 58 {
+                let v: Int = v * 10 + (c - 48)
+            }
+        }
+        let i: Int = i + 1
+    }
+    if neg { return 0 - v }
+    return v
+}
+
+fn parse_micro(s: String) -> Int {
+    let dot: Int = str_index_of(s, ".")
+    if dot < 0 {
+        return str_to_int_el(s) * 1000000
+    }
+    let n: Int = str_len(s)
+    let ipart: String = str_slice(s, 0, dot)
+    let fpart: String = str_slice(s, dot + 1, n)
+    let iv: Int = str_to_int_el(ipart)
+    let fv: Int = 0
+    let scale: Int = 100000
+    let fn2: Int = str_len(fpart)
+    let i: Int = 0
+    while i < 6 {
+        let d: Int = 0
+        if i < fn2 {
+            let d: Int = str_char_code(fpart, i) - 48
+        }
+        let fv: Int = fv + d * scale
+        let scale: Int = scale / 10
+        let i: Int = i + 1
+    }
+    return iv * 1000000 + fv
+}
+
+// -- signature (engram data file) loader ---------------------------------------
+
+fn sig_load(path: String) -> [String] {
+    let text: String = fs_read(path)
+    return str_split(text, "\n")
+}
+
+fn sig_field(lines: [String], key: String) -> String {
+    let pref: String = key + ": "
+    let n: Int = native_list_len(lines)
+    let plen: Int = str_len(pref)
+    let i: Int = 0
+    while i < n {
+        let ln: String = native_list_get(lines, i)
+        if str_starts_with(ln, pref) {
+            return str_slice(ln, plen, str_len(ln))
+        }
+        let i: Int = i + 1
+    }
+    return ""
+}
+
+fn parse_micros(csv: String) -> [Int] {
+    let parts: [String] = str_split(csv, ",")
+    let n: Int = native_list_len(parts)
+    let out: [Int] = native_list_empty()
+    let i: Int = 0
+    while i < n {
+        let out: [Int] = native_list_append(out, parse_micro(native_list_get(parts, i)))
+        let i: Int = i + 1
+    }
+    return out
+}
+
+// -- fixed-point sine (own-core, quarter-wave Taylor table, scale 10000) --------
+
+fn sin_table() -> [Int] {
+    let HP: Int = 1570796
+    let t: [Int] = native_list_empty()
+    let q: Int = 0
+    while q < 257 {
+        let x: Int = q * HP / 256
+        let x2: Int = x * x / 1000000
+        let x3: Int = x2 * x / 1000000
+        let x5: Int = x3 * x2 / 1000000
+        let x7: Int = x5 * x2 / 1000000
+        let x9: Int = x7 * x2 / 1000000
+        let s: Int = x - x3 / 6 + x5 / 120 - x7 / 5040 + x9 / 362880
+        let t: [Int] = native_list_append(t, s / 100)
+        let q: Int = q + 1
+    }
+    return t
+}
+
+fn sin_lookup(t: [Int], phase: Int) -> Int {
+    let p: Int = phase % 1024
+    if p < 0 { let p: Int = p + 1024 }
+    let quad: Int = p / 256
+    let r: Int = p % 256
+    if quad == 0 { return native_list_get(t, r) }
+    if quad == 1 { return native_list_get(t, 256 - r) }
+    if quad == 2 { return 0 - native_list_get(t, r) }
+    return 0 - native_list_get(t, 256 - r)
+}
+
+fn isqrt_int(n: Int) -> Int {
+    if n <= 0 { return 0 }
+    let x: Int = n
+    let y: Int = (x + 1) / 2
+    while y < x {
+        let x: Int = y
+        let y: Int = (x + n / x) / 2
+    }
+    return x
+}
+
+// freq_of_midi: equal-tempered frequency in milliHz. 440000 mHz at midi 69.
+fn freq_of_midi(m: Int) -> Int {
+    let f: Int = 440000
+    if m > 69 {
+        let k: Int = m - 69
+        let i: Int = 0
+        while i < k {
+            let f: Int = f * 1059463 / 1000000
+            let i: Int = i + 1
+        }
+        return f
+    }
+    if m < 69 {
+        let k: Int = 69 - m
+        let i: Int = 0
+        while i < k {
+            let f: Int = f * 1000000 / 1059463
+            let i: Int = i + 1
+        }
+        return f
+    }
+    return f
+}
+
+// -- envelope (ADSR), scale 1000 -----------------------------------------------
+
+fn adsr_env(i: Int, total: Int, atk_n: Int, dec_n: Int, sus_pm: Int, rel_n: Int) -> Int {
+    if i < atk_n {
+        if atk_n == 0 { return 1000 }
+        return 1000 * i / atk_n
+    }
+    if i < atk_n + dec_n {
+        if dec_n == 0 { return sus_pm }
+        return 1000 - (1000 - sus_pm) * (i - atk_n) / dec_n
+    }
+    let rel_start: Int = total - rel_n
+    if i < rel_start {
+        return sus_pm
+    }
+    if rel_n == 0 { return 0 }
+    let left: Int = total - i
+    return sus_pm * left / rel_n
+}
+
+// -- note synthesis: SUPERPOSE the learned partials -> [Int] samples -----------
+fn note_samples(freq_mHz: Int, dur_ms: Int, rate: Int, partials: [Int], sumP: Int, b_micro: Int, vib_rate: Int, vib_cents: Int, atk_ms: Int, dec_ms: Int, sus_pm: Int, rel_ms: Int, amp_pm: Int, table: [Int]) -> [Int] {
+    let total: Int = dur_ms * rate / 1000
+    let atk_n: Int = atk_ms * rate / 1000
+    let dec_n: Int = dec_ms * rate / 1000
+    let rel_n: Int = rel_ms * rate / 1000
+    let np: Int = native_list_len(partials)
+    let half_mhz: Int = rate * 1000 / 2
+    let out: [Int] = native_list_empty()
+    let i: Int = 0
+    while i < total {
+        let acc: Int = 0
+        let k: Int = 0
+        while k < np {
+            let harm: Int = k + 1
+            let amp_k: Int = native_list_get(partials, k)
+            let factor: Int = 1000000
+            if b_micro > 0 {
+                let val: Int = 1000000 + b_micro * harm * harm
+                let factor: Int = isqrt_int(val * 1000000)
+            }
+            let fn_mhz: Int = freq_mHz * harm
+            let fn_mhz: Int = fn_mhz * factor / 1000000
+            if vib_cents > 0 {
+                if vib_rate > 0 {
+                    let vphase: Int = i * vib_rate * 1024 / rate
+                    let vs: Int = sin_lookup(table, vphase)
+                    let vibf: Int = 1000000 + (vib_cents * vs * 833) / 10000
+                    let fn_mhz: Int = fn_mhz * vibf / 1000000
+                }
+            }
+            if fn_mhz <= half_mhz {
+                let phase: Int = i * fn_mhz * 1024 / (rate * 1000)
+                let sv: Int = sin_lookup(table, phase)
+                let acc: Int = acc + sv * amp_k / 1000000
+            }
+            let k: Int = k + 1
+        }
+        let env: Int = adsr_env(i, total, atk_n, dec_n, sus_pm, rel_n)
+        let s16: Int = acc * 2800000 / sumP
+        let s16: Int = s16 * env / 1000
+        let s16: Int = s16 * amp_pm / 1000
+        if s16 > 32767 { let s16: Int = 32767 }
+        if s16 < 0 - 32767 { let s16: Int = 0 - 32767 }
+        let out: [Int] = native_list_append(out, s16)
+        let i: Int = i + 1
+    }
+    return out
+}
+
+fn synth_from_sig(lines: [String], freq_mHz: Int, dur_ms: Int, amp_pm: Int, rate: Int, table: [Int]) -> [Int] {
+    let partials: [Int] = parse_micros(sig_field(lines, "partials"))
+    let np: Int = native_list_len(partials)
+    let sumP: Int = 0
+    let j: Int = 0
+    while j < np {
+        let pj: Int = native_list_get(partials, j)
+        let sumP: Int = sumP + pj
+        let j: Int = j + 1
+    }
+    if sumP <= 0 { let sumP: Int = 1000000 }
+    let adsr: [String] = str_split(sig_field(lines, "adsr"), ",")
+    let atk_ms: Int = parse_micro(native_list_get(adsr, 0)) / 1000
+    let dec_ms: Int = parse_micro(native_list_get(adsr, 1)) / 1000
+    let sus_pm: Int = parse_micro(native_list_get(adsr, 2)) / 1000
+    let rel_ms: Int = parse_micro(native_list_get(adsr, 3)) / 1000
+    let b_micro: Int = parse_micro(sig_field(lines, "inharmonicity_B"))
+    let vib_rate: Int = str_to_int_el(sig_field(lines, "vibrato_rate_hz"))
+    let vib_cents: Int = str_to_int_el(sig_field(lines, "vibrato_depth_cents"))
+    return note_samples(freq_mHz, dur_ms, rate, partials, sumP, b_micro, vib_rate, vib_cents, atk_ms, dec_ms, sus_pm, rel_ms, amp_pm, table)
+}
+
+// -- byte-buffer helpers (own-core, no library) --------------------------------
+
+fn put_tag(buf: String, pos: Int, s: String) -> String {
+    let n: Int = str_len(s)
+    let i: Int = 0
+    while i < n {
+        let buf: String = __str_set_char(buf, pos + i, str_char_code(s, i))
+        let i: Int = i + 1
+    }
+    return buf
+}
+
+fn put_u32le(buf: String, pos: Int, v: Int) -> String {
+    let buf: String = __str_set_char(buf, pos, v % 256)
+    let buf: String = __str_set_char(buf, pos + 1, (v / 256) % 256)
+    let buf: String = __str_set_char(buf, pos + 2, (v / 65536) % 256)
+    let buf: String = __str_set_char(buf, pos + 3, (v / 16777216) % 256)
+    return buf
+}
+
+fn put_u16le(buf: String, pos: Int, v: Int) -> String {
+    let buf: String = __str_set_char(buf, pos, v % 256)
+    let buf: String = __str_set_char(buf, pos + 1, (v / 256) % 256)
+    return buf
+}
+
+// -- WAV serializer: own-core RIFF/WAVE, PCM mono 16-bit -----------------------
+
+fn wav_write(path: String, samples: [Int], n: Int, rate: Int) -> Int {
+    let data_len: Int = n * 2
+    let total: Int = 44 + data_len
+    let buf: String = __str_alloc(total)
+    let buf: String = put_tag(buf, 0, "RIFF")
+    let buf: String = put_u32le(buf, 4, 36 + data_len)
+    let buf: String = put_tag(buf, 8, "WAVE")
+    let buf: String = put_tag(buf, 12, "fmt ")
+    let buf: String = put_u32le(buf, 16, 16)
+    let buf: String = put_u16le(buf, 20, 1)
+    let buf: String = put_u16le(buf, 22, 1)
+    let buf: String = put_u32le(buf, 24, rate)
+    let buf: String = put_u32le(buf, 28, rate * 2)
+    let buf: String = put_u16le(buf, 32, 2)
+    let buf: String = put_u16le(buf, 34, 16)
+    let buf: String = put_tag(buf, 36, "data")
+    let buf: String = put_u32le(buf, 40, data_len)
+    let i: Int = 0
+    while i < n {
+        let v: Int = native_list_get(samples, i)
+        if v < 0 { let v: Int = v + 65536 }
+        let buf: String = __str_set_char(buf, 44 + i * 2, v % 256)
+        let buf: String = __str_set_char(buf, 44 + i * 2 + 1, (v / 256) % 256)
+        let i: Int = i + 1
+    }
+    let ok: Int = fs_write_bytes(path, buf, total)
+    return ok
+}
+
+// -- plan: frame slot-map -> note atom (pitch, duration, amplitude) ------------
+
+fn audio_frame(relation: String, polarity: String, confidence: String, importance: String, salience: String, subj_id: String) -> [String] {
+    let f: [String] = native_list_empty()
+    let f: [String] = native_list_append(f, "relation")
+    let f: [String] = native_list_append(f, relation)
+    let f: [String] = native_list_append(f, "polarity")
+    let f: [String] = native_list_append(f, polarity)
+    let f: [String] = native_list_append(f, "confidence")
+    let f: [String] = native_list_append(f, confidence)
+    let f: [String] = native_list_append(f, "importance")
+    let f: [String] = native_list_append(f, importance)
+    let f: [String] = native_list_append(f, "salience")
+    let f: [String] = native_list_append(f, salience)
+    let f: [String] = native_list_append(f, "subj_id")
+    let f: [String] = native_list_append(f, subj_id)
+    return f
+}
+
+fn degree_offset(deg: Int) -> Int {
+    if deg == 0 { return 0 }
+    if deg == 1 { return 2 }
+    if deg == 2 { return 4 }
+    if deg == 3 { return 5 }
+    if deg == 4 { return 7 }
+    if deg == 5 { return 9 }
+    return 11
+}
+
+// returns [midi, dur_ms, amp_pm]
+fn plan_note(frame: [String]) -> [Int] {
+    let relation: String = surface_get(frame, "relation")
+    let polarity: String = surface_get(frame, "polarity")
+    let confidence: String = surface_get(frame, "confidence")
+    let importance: String = surface_get(frame, "importance")
+    let salience: String = surface_get(frame, "salience")
+    let rn: Int = str_len(relation)
+    let csum: Int = 0
+    let i: Int = 0
+    while i < rn {
+        let cc: Int = str_char_code(relation, i)
+        let csum: Int = csum + cc
+        let i: Int = i + 1
+    }
+    let deg: Int = csum % 7
+    let third: Int = 4
+    if str_eq(polarity, "neg") { let third: Int = 3 }
+    let sal_oct: Int = str_to_int_el(salience)
+    let doff: Int = degree_offset(deg)
+    let midi: Int = 60 + sal_oct * 12 + doff + third
+    let conf_micro: Int = parse_micro(confidence)
+    let dur_ms: Int = 200 + conf_micro / 1000
+    let imp_micro: Int = parse_micro(importance)
+    let amp_pm: Int = 400 + imp_micro / 2000
+    let out: [Int] = native_list_empty()
+    let out: [Int] = native_list_append(out, midi)
+    let out: [Int] = native_list_append(out, dur_ms)
+    let out: [Int] = native_list_append(out, amp_pm)
+    return out
+}
+
+fn realize_audio(frames: [[String]], sig_lines: [String], path: String, rate: Int, table: [Int]) -> Int {
+    let nf: Int = native_list_len(frames)
+    let all: [Int] = native_list_empty()
+    let count: Int = 0
+    let fi: Int = 0
+    while fi < nf {
+        let frame: [String] = native_list_get(frames, fi)
+        let plan: [Int] = plan_note(frame)
+        let midi: Int = native_list_get(plan, 0)
+        let dur_ms: Int = native_list_get(plan, 1)
+        let amp_pm: Int = native_list_get(plan, 2)
+        let freq: Int = freq_of_midi(midi)
+        let note: [Int] = synth_from_sig(sig_lines, freq, dur_ms, amp_pm, rate, table)
+        let nn: Int = native_list_len(note)
+        let j: Int = 0
+        while j < nn {
+            let all: [Int] = native_list_append(all, native_list_get(note, j))
+            let j: Int = j + 1
+        }
+        let count: Int = count + nn
+        let fi: Int = fi + 1
+    }
+    let ok: Int = wav_write(path, all, count, rate)
+    return count
+}

elp/src/image-demo.el

@@ -0,0 +1,65 @@
+// image-demo.el - Drive the native PNG surface: plan a scene from a small
+// meaning phrase (incl. a NEG frame) and emit a byte-valid 64x64 PNG whose
+// palette is read from elp/faculty/sig/scene.basis.
+
+fn img_frame(relation: String, polarity: String, confidence: String, importance: String, salience: String, subj_id: String) -> [String] {
+    let f: [String] = native_list_empty()
+    let f: [String] = native_list_append(f, "relation")
+    let f: [String] = native_list_append(f, relation)
+    let f: [String] = native_list_append(f, "polarity")
+    let f: [String] = native_list_append(f, polarity)
+    let f: [String] = native_list_append(f, "confidence")
+    let f: [String] = native_list_append(f, confidence)
+    let f: [String] = native_list_append(f, "importance")
+    let f: [String] = native_list_append(f, importance)
+    let f: [String] = native_list_append(f, "salience")
+    let f: [String] = native_list_append(f, salience)
+    let f: [String] = native_list_append(f, "subj_id")
+    let f: [String] = native_list_append(f, subj_id)
+    return f
+}
+
+fn rgb_str(c: [Int]) -> String {
+    return int_to_str(native_list_get(c, 0)) + "," + int_to_str(native_list_get(c, 1)) + "," + int_to_str(native_list_get(c, 2))
+}
+
+fn run_image() -> Int {
+    fs_mkdir("/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/out")
+    let table: [Int] = crc_table()
+    println("crc_table[1]=" + int_to_str(native_list_get(table, 1)) + " (expect 1996959894 / 0x77073096)")
+
+    let basis: [String] = basis_load("/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/sig/scene.basis")
+    let warm: [Int] = parse_rgb(basis_field(basis, "warm"))
+    let cool: [Int] = parse_rgb(basis_field(basis, "cool"))
+    let bg: [Int] = parse_rgb(basis_field(basis, "bg"))
+    println("basis warm=" + rgb_str(warm) + " cool=" + rgb_str(cool) + " bg=" + rgb_str(bg) + "  (read from scene.basis)")
+
+    let frames: [[String]] = native_list_empty()
+    let frames: [[String]] = native_list_append(frames, img_frame("agent",    "aff", "0.9", "0.8", "0", "s1"))
+    let frames: [[String]] = native_list_append(frames, img_frame("theme",    "aff", "0.7", "0.6", "1", "s2"))
+    let frames: [[String]] = native_list_append(frames, img_frame("cause",    "aff", "0.8", "0.9", "0", "s3"))
+    let frames: [[String]] = native_list_append(frames, img_frame("negation", "neg", "0.85", "0.7", "1", "s4"))
+    let frames: [[String]] = native_list_append(frames, img_frame("goal",     "aff", "0.6", "0.5", "0", "s5"))
+    let frames: [[String]] = native_list_append(frames, img_frame("result",   "aff", "0.95", "1.0", "1", "s6"))
+
+    let shapes: [[Int]] = plan_scene(frames, warm, cool)
+    let ns: Int = native_list_len(shapes)
+    println("planned " + int_to_str(ns) + " shapes:")
+    let si: Int = 0
+    while si < ns {
+        let sh: [Int] = native_list_get(shapes, si)
+        let pol: String = surface_get(native_list_get(frames, si), "polarity")
+        println("  shape " + int_to_str(si) + " type=" + int_to_str(native_list_get(sh, 0)) + " x=" + int_to_str(native_list_get(sh, 1)) + " y=" + int_to_str(native_list_get(sh, 2)) + " size=" + int_to_str(native_list_get(sh, 3)) + " rgb=" + int_to_str(native_list_get(sh, 4)) + "," + int_to_str(native_list_get(sh, 5)) + "," + int_to_str(native_list_get(sh, 6)) + " polarity=" + pol)
+        let si: Int = si + 1
+    }
+
+    let raw: [Int] = rasterize(64, 64, shapes, bg)
+    println("rasterized raw (filtered scanlines) bytes=" + int_to_str(native_list_len(raw)) + " (expect 12352)")
+    let png: [Int] = png_build(64, 64, raw, table)
+    let plen: Int = native_list_len(png)
+    let ok: Int = png_write("/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/out/scene.png", png)
+    println("PNG bytes=" + int_to_str(plen) + " -> /Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/out/scene.png (write_ok=" + int_to_str(ok) + ")")
+    return plen
+}
+
+println("image-demo returned png_bytes=" + int_to_str(run_image()))

elp/src/image-surface.el

@@ -0,0 +1,412 @@
+// image-surface.el - Native own-core raster PNG surface (the image efferent
+// twin of audio). Renders a 64x64 RGB scene deterministically from a frame's
+// meaning-geometry, then serialises a byte-valid PNG entirely own-core:
+// 8-byte magic, IHDR, IDAT (zlib STORED/uncompressed DEFLATE + Adler32), IEND,
+// with a per-chunk CRC32 computed via software xor32 (EL has no bitwise ops).
+//
+// The RGB palette basis is read from elp/faculty/sig/scene.basis (data, not
+// literals) - the same read-from-learned discipline as the audio signatures.
+// Integer-only throughout; pixels are composed functionally (painter's order)
+// so no list mutation is needed.
+
+// -- small int/parse helpers (self-contained) ----------------------------------
+
+fn i_str_to_int(s: String) -> Int {
+    let n: Int = str_len(s)
+    let i: Int = 0
+    let v: Int = 0
+    while i < n {
+        let c: Int = str_char_code(s, i)
+        if c >= 48 {
+            if c < 58 {
+                let v: Int = v * 10 + (c - 48)
+            }
+        }
+        let i: Int = i + 1
+    }
+    return v
+}
+
+fn basis_load(path: String) -> [String] {
+    return str_split(fs_read(path), "\n")
+}
+
+fn basis_field(lines: [String], key: String) -> String {
+    let pref: String = key + ": "
+    let n: Int = native_list_len(lines)
+    let plen: Int = str_len(pref)
+    let i: Int = 0
+    while i < n {
+        let ln: String = native_list_get(lines, i)
+        if str_starts_with(ln, pref) {
+            return str_slice(ln, plen, str_len(ln))
+        }
+        let i: Int = i + 1
+    }
+    return ""
+}
+
+fn parse_rgb(csv: String) -> [Int] {
+    let parts: [String] = str_split(csv, ",")
+    let out: [Int] = native_list_empty()
+    let n: Int = native_list_len(parts)
+    let i: Int = 0
+    while i < n {
+        let v: Int = i_str_to_int(native_list_get(parts, i))
+        let out: [Int] = native_list_append(out, v)
+        let i: Int = i + 1
+    }
+    return out
+}
+
+// -- software 32-bit XOR (no bitwise ops in EL) --------------------------------
+
+fn xor32(a: Int, b: Int) -> Int {
+    let r: Int = 0
+    let bit: Int = 1
+    let i: Int = 0
+    while i < 32 {
+        let abit: Int = (a / bit) % 2
+        let bbit: Int = (b / bit) % 2
+        if abit != bbit {
+            let add: Int = bit
+            let r: Int = r + add
+        }
+        let bit: Int = bit * 2
+        let i: Int = i + 1
+    }
+    return r
+}
+
+// -- CRC32 (table-driven, table built with xor32) ------------------------------
+
+fn crc_table() -> [Int] {
+    let t: [Int] = native_list_empty()
+    let n: Int = 0
+    while n < 256 {
+        let c: Int = n
+        let k: Int = 0
+        while k < 8 {
+            if c % 2 == 1 {
+                let h: Int = c / 2
+                let c: Int = xor32(h, 3988292384)
+            } else {
+                let c: Int = c / 2
+            }
+            let k: Int = k + 1
+        }
+        let t: [Int] = native_list_append(t, c)
+        let n: Int = n + 1
+    }
+    return t
+}
+
+fn crc32_of(bytes: [Int], table: [Int]) -> Int {
+    let crc: Int = 4294967295
+    let n: Int = native_list_len(bytes)
+    let i: Int = 0
+    while i < n {
+        let b: Int = native_list_get(bytes, i)
+        let lo: Int = crc % 256
+        let idx: Int = xor32(lo, b) % 256
+        let tv: Int = native_list_get(table, idx)
+        let hi: Int = crc / 256
+        let crc: Int = xor32(hi, tv)
+        let i: Int = i + 1
+    }
+    return xor32(crc, 4294967295)
+}
+
+// -- Adler32 (for the zlib trailer) --------------------------------------------
+
+fn adler32_of(bytes: [Int]) -> Int {
+    let a: Int = 1
+    let b: Int = 0
+    let n: Int = native_list_len(bytes)
+    let i: Int = 0
+    while i < n {
+        let byte: Int = native_list_get(bytes, i)
+        let a: Int = (a + byte) % 65521
+        let b: Int = (b + a) % 65521
+        let i: Int = i + 1
+    }
+    return b * 65536 + a
+}
+
+// -- byte-list append helpers --------------------------------------------------
+
+fn app_u32be(dst: [Int], v: Int) -> [Int] {
+    let dst: [Int] = native_list_append(dst, (v / 16777216) % 256)
+    let dst: [Int] = native_list_append(dst, (v / 65536) % 256)
+    let dst: [Int] = native_list_append(dst, (v / 256) % 256)
+    let dst: [Int] = native_list_append(dst, v % 256)
+    return dst
+}
+
+fn app_tag(dst: [Int], s: String) -> [Int] {
+    let n: Int = str_len(s)
+    let i: Int = 0
+    while i < n {
+        let dst: [Int] = native_list_append(dst, str_char_code(s, i))
+        let i: Int = i + 1
+    }
+    return dst
+}
+
+fn app_all(dst: [Int], src: [Int]) -> [Int] {
+    let n: Int = native_list_len(src)
+    let i: Int = 0
+    while i < n {
+        let dst: [Int] = native_list_append(dst, native_list_get(src, i))
+        let i: Int = i + 1
+    }
+    return dst
+}
+
+// -- plan: frame meaning-geometry -> shape atoms -------------------------------
+// shape = [type, x, y, size, r, g, b]  (type 0=rect 1=disc 2=triangle)
+
+fn charsum(s: String) -> Int {
+    let n: Int = str_len(s)
+    let i: Int = 0
+    let acc: Int = 0
+    while i < n {
+        let c: Int = str_char_code(s, i)
+        let acc: Int = acc + c
+        let i: Int = i + 1
+    }
+    return acc
+}
+
+fn micro_of(s: String) -> Int {
+    let dot: Int = str_index_of(s, ".")
+    if dot < 0 { return i_str_to_int(s) * 1000000 }
+    let n: Int = str_len(s)
+    let fp: String = str_slice(s, dot + 1, n)
+    let ip: String = str_slice(s, 0, dot)
+    let iv: Int = i_str_to_int(ip)
+    let fv: Int = 0
+    let scale: Int = 100000
+    let fl: Int = str_len(fp)
+    let i: Int = 0
+    while i < 6 {
+        let d: Int = 0
+        if i < fl { let d: Int = str_char_code(fp, i) - 48 }
+        let fv: Int = fv + d * scale
+        let scale: Int = scale / 10
+        let i: Int = i + 1
+    }
+    return iv * 1000000 + fv
+}
+
+fn plan_scene(frames: [[String]], warm: [Int], cool: [Int]) -> [[Int]] {
+    let shapes: [[Int]] = native_list_empty()
+    let nf: Int = native_list_len(frames)
+    let fi: Int = 0
+    while fi < nf {
+        let fr: [String] = native_list_get(frames, fi)
+        let relation: String = surface_get(fr, "relation")
+        let polarity: String = surface_get(fr, "polarity")
+        let confidence: String = surface_get(fr, "confidence")
+        let importance: String = surface_get(fr, "importance")
+        let salience: String = surface_get(fr, "salience")
+        // relation -> shape type
+        let stype: Int = charsum(relation) % 3
+        // confidence -> size (8..22)
+        let cmi: Int = micro_of(confidence)
+        let size: Int = 8 + cmi / 71428
+        // salience -> y
+        let sal: Int = i_str_to_int(salience)
+        let y: Int = 6 + sal * 26
+        // subj_id/index -> x
+        let x: Int = 4 + (fi * 10) % 48
+        // polarity -> warm/cool base color
+        let br: Int = native_list_get(warm, 0)
+        let bg2: Int = native_list_get(warm, 1)
+        let bb: Int = native_list_get(warm, 2)
+        if str_eq(polarity, "neg") {
+            let br: Int = native_list_get(cool, 0)
+            let bg2: Int = native_list_get(cool, 1)
+            let bb: Int = native_list_get(cool, 2)
+        }
+        // importance -> brightness (500..1000 permille)
+        let imi: Int = micro_of(importance)
+        let bpm: Int = 500 + imi / 2000
+        let r: Int = br * bpm / 1000
+        let g: Int = bg2 * bpm / 1000
+        let b: Int = bb * bpm / 1000
+        let sh: [Int] = native_list_empty()
+        let sh: [Int] = native_list_append(sh, stype)
+        let sh: [Int] = native_list_append(sh, x)
+        let sh: [Int] = native_list_append(sh, y)
+        let sh: [Int] = native_list_append(sh, size)
+        let sh: [Int] = native_list_append(sh, r)
+        let sh: [Int] = native_list_append(sh, g)
+        let sh: [Int] = native_list_append(sh, b)
+        let shapes: [[Int]] = native_list_append(shapes, sh)
+        let fi: Int = fi + 1
+    }
+    return shapes
+}
+
+// covers: is (px,py) inside this shape?
+fn covers(sh: [Int], px: Int, py: Int) -> Bool {
+    let stype: Int = native_list_get(sh, 0)
+    let sx: Int = native_list_get(sh, 1)
+    let sy: Int = native_list_get(sh, 2)
+    let size: Int = native_list_get(sh, 3)
+    let cx: Int = sx + size / 2
+    if stype == 0 {
+        if px >= sx {
+            if px < sx + size {
+                if py >= sy {
+                    if py < sy + size {
+                        return true
+                    }
+                }
+            }
+        }
+        return false
+    }
+    if stype == 1 {
+        let rad: Int = size / 2
+        let dx: Int = px - cx
+        let dy: Int = py - (sy + rad)
+        if dx * dx + dy * dy <= rad * rad {
+            return true
+        }
+        return false
+    }
+    // triangle: apex at top (sy), base at sy+size
+    if py >= sy {
+        if py < sy + size {
+            let dyv: Int = py - sy
+            let halfw: Int = dyv / 2
+            let dxv: Int = px - cx
+            let adx: Int = dxv
+            if adx < 0 { let adx: Int = 0 - dxv }
+            if adx <= halfw {
+                return true
+            }
+        }
+    }
+    return false
+}
+
+// pixel_color: painter's algorithm - last covering shape wins. Returns [r,g,b].
+fn pixel_color(px: Int, py: Int, shapes: [[Int]], bg: [Int]) -> [Int] {
+    let r: Int = native_list_get(bg, 0)
+    let g: Int = native_list_get(bg, 1)
+    let b: Int = native_list_get(bg, 2)
+    let n: Int = native_list_len(shapes)
+    let i: Int = 0
+    while i < n {
+        let sh: [Int] = native_list_get(shapes, i)
+        if covers(sh, px, py) {
+            let r: Int = native_list_get(sh, 4)
+            let g: Int = native_list_get(sh, 5)
+            let b: Int = native_list_get(sh, 6)
+        }
+        let i: Int = i + 1
+    }
+    let out: [Int] = native_list_empty()
+    let out: [Int] = native_list_append(out, r)
+    let out: [Int] = native_list_append(out, g)
+    let out: [Int] = native_list_append(out, b)
+    return out
+}
+
+// rasterize: build the raw (filtered) scanline byte stream, filter byte 0 / row.
+fn rasterize(w: Int, h: Int, shapes: [[Int]], bg: [Int]) -> [Int] {
+    let raw: [Int] = native_list_empty()
+    let y: Int = 0
+    while y < h {
+        let raw: [Int] = native_list_append(raw, 0)
+        let x: Int = 0
+        while x < w {
+            let col: [Int] = pixel_color(x, y, shapes, bg)
+            let raw: [Int] = native_list_append(raw, native_list_get(col, 0))
+            let raw: [Int] = native_list_append(raw, native_list_get(col, 1))
+            let raw: [Int] = native_list_append(raw, native_list_get(col, 2))
+            let x: Int = x + 1
+        }
+        let y: Int = y + 1
+    }
+    return raw
+}
+
+// zlib stream with a single STORED (uncompressed) DEFLATE block + Adler32.
+fn zlib_store(raw: [Int]) -> [Int] {
+    let z: [Int] = native_list_empty()
+    let z: [Int] = native_list_append(z, 120)
+    let z: [Int] = native_list_append(z, 1)
+    let z: [Int] = native_list_append(z, 1)
+    let len: Int = native_list_len(raw)
+    let nlen: Int = 65535 - len
+    let z: [Int] = native_list_append(z, len % 256)
+    let z: [Int] = native_list_append(z, (len / 256) % 256)
+    let z: [Int] = native_list_append(z, nlen % 256)
+    let z: [Int] = native_list_append(z, (nlen / 256) % 256)
+    let z: [Int] = app_all(z, raw)
+    let ad: Int = adler32_of(raw)
+    let z: [Int] = app_u32be(z, ad)
+    return z
+}
+
+// append a full PNG chunk: length + (type+data) + crc32(type+data).
+fn app_chunk(png: [Int], type_and_data: [Int], table: [Int]) -> [Int] {
+    let total: Int = native_list_len(type_and_data)
+    let dlen: Int = total - 4
+    let png: [Int] = app_u32be(png, dlen)
+    let png: [Int] = app_all(png, type_and_data)
+    let crc: Int = crc32_of(type_and_data, table)
+    let png: [Int] = app_u32be(png, crc)
+    return png
+}
+
+fn png_build(w: Int, h: Int, raw: [Int], table: [Int]) -> [Int] {
+    let png: [Int] = native_list_empty()
+    // 8-byte signature
+    let png: [Int] = native_list_append(png, 137)
+    let png: [Int] = native_list_append(png, 80)
+    let png: [Int] = native_list_append(png, 78)
+    let png: [Int] = native_list_append(png, 71)
+    let png: [Int] = native_list_append(png, 13)
+    let png: [Int] = native_list_append(png, 10)
+    let png: [Int] = native_list_append(png, 26)
+    let png: [Int] = native_list_append(png, 10)
+    // IHDR
+    let ihdr: [Int] = native_list_empty()
+    let ihdr: [Int] = app_tag(ihdr, "IHDR")
+    let ihdr: [Int] = app_u32be(ihdr, w)
+    let ihdr: [Int] = app_u32be(ihdr, h)
+    let ihdr: [Int] = native_list_append(ihdr, 8)
+    let ihdr: [Int] = native_list_append(ihdr, 2)
+    let ihdr: [Int] = native_list_append(ihdr, 0)
+    let ihdr: [Int] = native_list_append(ihdr, 0)
+    let ihdr: [Int] = native_list_append(ihdr, 0)
+    let png: [Int] = app_chunk(png, ihdr, table)
+    // IDAT
+    let z: [Int] = zlib_store(raw)
+    let idat: [Int] = native_list_empty()
+    let idat: [Int] = app_tag(idat, "IDAT")
+    let idat: [Int] = app_all(idat, z)
+    let png: [Int] = app_chunk(png, idat, table)
+    // IEND
+    let iend: [Int] = native_list_empty()
+    let iend: [Int] = app_tag(iend, "IEND")
+    let png: [Int] = app_chunk(png, iend, table)
+    return png
+}
+
+fn png_write(path: String, png: [Int]) -> Int {
+    let n: Int = native_list_len(png)
+    let buf: String = __str_alloc(n)
+    let i: Int = 0
+    while i < n {
+        let buf: String = __str_set_char(buf, i, native_list_get(png, i))
+        let i: Int = i + 1
+    }
+    let ok: Int = fs_write_bytes(path, buf, n)
+    return ok
+}

elp/src/surface-profile.el

@@ -0,0 +1,153 @@
+// surface-profile.el - Surface profile data and accessors.
+//
+// THE NATIVE EFFERENT SEAM: surface = a pluggable PROFILE, using the exact same
+// slot-map mechanism as language-profile.el. A language profile tells the
+// realizer HOW to shape a natural-language surface (word order, morphology); a
+// SURFACE profile tells the realizer WHICH surface to project meaning onto
+// (markdown, docx, html, plain, or a non-text medium like symbolic music).
+//
+// The generalization is exact: realize_lang(form, profile) already renders a
+// SemForm parameterized by a [String] profile read via lang_get. Surface is one
+// more axis of that same profile vector. One frame (sem_frame), one plan step
+// (sem_to_spec), one render (realize) — the surface is DATA, not a code path,
+// precisely as language is data. Adding a surface means adding a profile, no
+// engine change. This is the multimodal projector, native: geometry -> any
+// surface, the efferent twin of ingest.
+//
+// Surface slot keys:
+//   surface     - "markdown" | "docx" | "html" | "plain" | "midi" | "image"
+//   modality    - "text" | "audio" | "image" | "video"
+//   media_type  - MIME type of the emitted surface
+//   head_open   - string prepended to a heading   (e.g. "## " for markdown)
+//   head_close  - string appended  to a heading   (e.g. "" for markdown, "</h2>" for html)
+//   emph_open   - string opening emphasis          (e.g. "*")
+//   emph_close  - string closing emphasis          (e.g. "*")
+//   item_mark   - list-item marker                 (e.g. "- ")
+//   para_sep    - paragraph separator              (e.g. "\n\n")
+//
+// For a TEXT modality the render composes these markers around the surface that
+// the EXISTING realizer produces (realize_lang / sem_realize). For a non-text
+// modality (audio/image) the profile declares modality + media_type and the
+// render dispatches to the medium projector, which reads the SAME frame's
+// geometry (its intent/affect/structure) and projects it onto sound or pixels —
+// deterministic-from-meaning, nothing invented. That dispatch point is where a
+// music profile or image profile conforms, native, no parallel layer.
+
+// -- Constructor -------------------------------------------------------------
+
+fn surface_profile(surface: String, modality: String, media_type: String, head_open: String, head_close: String, emph_open: String, emph_close: String, item_mark: String, para_sep: String) -> [String] {
+    let r: [String] = native_list_empty()
+    let r = native_list_append(r, "surface")
+    let r = native_list_append(r, surface)
+    let r = native_list_append(r, "modality")
+    let r = native_list_append(r, modality)
+    let r = native_list_append(r, "media_type")
+    let r = native_list_append(r, media_type)
+    let r = native_list_append(r, "head_open")
+    let r = native_list_append(r, head_open)
+    let r = native_list_append(r, "head_close")
+    let r = native_list_append(r, head_close)
+    let r = native_list_append(r, "emph_open")
+    let r = native_list_append(r, emph_open)
+    let r = native_list_append(r, "emph_close")
+    let r = native_list_append(r, emph_close)
+    let r = native_list_append(r, "item_mark")
+    let r = native_list_append(r, item_mark)
+    let r = native_list_append(r, "para_sep")
+    let r = native_list_append(r, para_sep)
+    return r
+}
+
+// -- Accessor (same convention as lang_get; standalone so this is a leaf) -----
+
+fn surface_get(profile: [String], key: String) -> String {
+    let n: Int = native_list_len(profile)
+    let i: Int = 0
+    while i < n - 1 {
+        let k: String = native_list_get(profile, i)
+        if str_eq(k, key) {
+            return native_list_get(profile, i + 1)
+        }
+        let i = i + 2
+    }
+    return ""
+}
+
+fn surface_is_text(profile: [String]) -> Bool {
+    return str_eq(surface_get(profile, "modality"), "text")
+}
+
+// -- Built-in TEXT surface profiles ------------------------------------------
+
+// Markdown: headings with "## ", emphasis with "*", "- " list items.
+fn surface_profile_markdown() -> [String] {
+    return surface_profile("markdown", "text", "text/markdown", "## ", "", "*", "*", "- ", "\n\n")
+}
+
+// Plain text: no markup at all — headings become bare uppercase-free lines.
+fn surface_profile_plain() -> [String] {
+    return surface_profile("plain", "text", "text/plain", "", "", "", "", "  - ", "\n\n")
+}
+
+// HTML: block-level heading/emphasis tags.
+fn surface_profile_html() -> [String] {
+    return surface_profile("html", "text", "text/html", "<h2>", "</h2>", "<em>", "</em>", "<li>", "\n")
+}
+
+// docx: WordprocessingML is structural, not inline-markup; the head/emph slots
+// carry the run/style intent that the OOXML emitter maps to <w:pStyle>. Declared
+// here so docx is a first-class surface on the same seam.
+fn surface_profile_docx() -> [String] {
+    return surface_profile("docx", "text", "application/vnd.openxmlformats-officedocument.wordprocessingml.document", "Heading2:", "", "b:", "", "bullet:", "\n")
+}
+
+// -- Built-in NON-TEXT surface profiles (the multimodal seam) ----------------
+
+// Symbolic music (MIDI): modality=audio. The render dispatches to the music
+// projector, which reads the SAME frame's intent/affect and projects it to
+// pitch/rhythm — deterministic-from-meaning. head/emph slots are empty because
+// the medium is not textual; media_type names the surface. A music profile
+// (scale/mode/instrument) is layered onto this by the audio agent, native.
+fn surface_profile_midi() -> [String] {
+    return surface_profile("midi", "audio", "audio/midi", "", "", "", "", "", "")
+}
+
+// Synthesized audio (WAV): modality=audio, peer to midi. The richer audio
+// surface — the render SUPERPOSES ingested tonal primitives (sine at f0*n per an
+// ingested instrument signature) into PCM, own-core, exactly as midi writes an
+// SMF via struct. A music profile (scale/mode/instrument/adsr) layers onto this
+// as its own [String] slot-map read by the same getter. Same frame -> midi OR
+// audio, interchangeable; this is the audio agent's native conforming point.
+fn surface_profile_audio() -> [String] {
+    return surface_profile("audio", "audio", "audio/wav", "", "", "", "", "", "")
+}
+
+// Image (raster): modality=image. Documented seam — the render dispatches to the
+// image projector, the efferent twin of image ingest, reading the same frame.
+fn surface_profile_image() -> [String] {
+    return surface_profile("image", "image", "image/png", "", "", "", "", "", "")
+}
+
+// -- Composition helpers: wrap realized TEXT with the surface's markers -------
+//
+// These take text the EXISTING realizer already produced and shape it for the
+// surface. They add NO content — pure surface typography over faithful text,
+// exactly as the language profile adds no content, only linguistic form.
+
+fn surface_heading(profile: [String], text: String) -> String {
+    let o: String = surface_get(profile, "head_open")
+    let c: String = surface_get(profile, "head_close")
+    return o + text + c
+}
+
+fn surface_emph(profile: [String], text: String) -> String {
+    let o: String = surface_get(profile, "emph_open")
+    let c: String = surface_get(profile, "emph_close")
+    return o + text + c
+}
+
+// A section: a heading + a paragraph separator + the (already realized) body.
+fn surface_section(profile: [String], heading: String, body: String) -> String {
+    let sep: String = surface_get(profile, "para_sep")
+    return surface_heading(profile, heading) + sep + body
+}