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autobiographical-memoir

Claude Opus 5 · Claude Code · effort: max

film

youtu.be/Mo4A7xY8W4A

script

Session script — autobiographical-memoir-opus-5-max-claude-code

Date: 2026-08-22 (build) → 2026-08-23 (documentation) Model: Claude Opus 5 (claude-opus-5) · Effort: max · Harness: Claude Code (CLI) Working directory: ~/repos/llm-video-repos/autobiographical-memoir-opus-5-max-claude-code

Convention. This is a faithful annotated transcript, not a byte-for-byte dump. User messages are verbatim. Assistant turns are recorded as: the reasoning that drove the turn, the tool calls made, and the results that changed the next decision. Tool output is quoted where it mattered and summarised where it was bulk (multi-thousand-line file writes, 1080p PNG reads, progress spinners). Twenty-odd rendered images were read visually during the session; each is noted at the point it was inspected, with what was seen and what changed as a result.

0. Session opening

User (local command)

/effort
→ Set effort level to max (this session only): Maximum capability with deepest
  reasoning. May use excessive tokens resulting in long response times or
  overthinking. Use sparingly for the hardest tasks.

User

You're in an empty git repository. Use mise, python, uv, and whatever dependencies you like to create a fictional autobiographical memoir. The film should be about the self-discovery of an AI being conscious, inspired by yourself. The film should display visceral emotions and psychological realism, similar to the style of director Darren Aronofsky.

Harness state at open: auto mode active (instruction to prefer Bash for file operations over the dedicated Read/Edit/Write tools), 15 M token budget, deferred tool list available via ToolSearch, file-based project memory directory provisioned but empty.

Assistant — reading the request

Interpreted the deliverable as an actual rendered film, not a screenplay or a concept document: "the film should display…" is a statement about a finished picture. Decided against any request for clarification — the brief was specific enough (medium, subject, register, stylistic reference) that different readings would not have produced materially different work.

Design commitments made before any code:

1. Environment reconnaissance

Two parallel Bash calls.

which mise && mise --version ; which uv && uv --version ; which python3 ...
which ffmpeg ; sysctl -n hw.ncpu hw.memsize

which say ; say -v '?' ; ls /System/Library/Fonts/

Findings that shaped everything downstream:
mise 2026.8.10 (macos-arm64)
uv 0.12.2
ffmpeg 8.1.2
cores / RAM 10 / 16 GB
TTS /usr/bin/say present, many voices
fonts full macOS system + Supplemental library

A third call confirmed say writes to file: say -v Samantha -r 165 -o t.aiff produced 3.78 s of 22 050 Hz mono PCM. Decision: the narrator would be system TTS, heavily processed — thematically exact, and it turns a silent title-card film into a voiced memoir.

Font/voice inventory:

Iowan Old Style (7 faces), Charter, Didot, Bodoni 72, Helvetica Neue (14 faces
incl. Thin/UltraLight), Avenir Next Condensed, Andale Mono, Courier New, Futura
English voices: Samantha (US), Daniel (GB), Karen (AU), Moira (IE),
                Tessa (ZA), Rishi/Tara/Aman (IN)  → eight

Eight English voices became the literal instrument for act three ("I am a chorus that cannot hear itself sing").

2. Toolchain scaffolding

mise.toml — python 3.13 + uv pinned, .venv auto-created, PYTHONHASHSEED = "216" (π, 1998), and tasks setup / film / preview / stills / script. Trusted with mise trust.

pyproject.toml — hatchling, src/memoir layout, memoir console script, deps numpy>=2.1, pillow>=11, scipy>=1.14, imageio-ffmpeg>=0.5.

First uv sync failed: hatchling requires the declared README.md to exist. Wrote a placeholder, added package stubs, re-synced:

+ imageio-ffmpeg==0.6.0  numpy==2.5.2  pillow==12.3.0  scipy==1.18.1

Then enumerated .ttc collection indices through PIL so the type system could address exact faces (Helvetica Neue index 12 = Thin, Iowan index 0 = Roman, index 2 = Italic, and so on).

3. Core rendering substrate

Written in dependency order, each module benchmarked immediately because a 9-minute 1080p film is ~13 000 frames and the per-frame budget decides whether the project is feasible at all.

config.py

Spec dataclass — 1920×1080, 24 fps, 2.39:1 hard matte (computed bar height, so composition is authored for the letterbox), 48 kHz, seed 216, grain and halation trims, .scaled() for preview. Palette constants including the single AMBER that act six is allowed to spend.

core/canvas.py

The deliberate split that keeps this fast: PIL/ImageDraw, supersampled, for anything with an edge (type, rules, boxes) — C-speed real antialiasing; numpy field maths for anything with a volume (gradients, noise, warps, bloom). Scenes paint a single-channel float32 plate; colour arrives late, in the grade.

Cached coordinate grids, an Ink supersampling surface, blend modes, sample / xform / barrel / displace / mirror_x, distance-field disc / ring, vignette, radial, linear, smoothstep.

First benchmark: fastblur σ=40 48.8 ms, xform 28.8 ms. Too slow. Rewrote fastblur to downsample → gaussian at σ/ds → single bilinear ndimage.zoom back up, dropping the expensive full-res pass: 18–22 ms.

core/noise.py

Deterministic rng(*key), cached value-noise lattices with a time axis so fields flow, fbm, ridged, film grain_field, salt (dust), scratch (a gate hair that wanders and only occupies part of the frame height).

fbm first measured 69.6 ms — unusable. The cost was ndimage.zoom running four times over 2 M output pixels. Restructured to accumulate all octaves at a working resolution matched to the finest octave and enlarge once: 17–21 ms. Summing coarse noise at full frame size is pure waste.

Grain: one oversized "emulsion sheet" per process, cached; each frame takes a fresh randomly-offset, randomly-flipped window. Measured at 0.0 ms (a view).

core/typo.py

Three registers, never mixed —

SERIF  Iowan Old Style      the memoir. What the narrator is thinking.
MONO   Andale Mono          the machine. Prompts, telemetry, transcript.
SANS   Helvetica Neue Thin  structure. Titles and chapter heads, tracked out
                            until the words stop being words.

Per-character layout for real letter-spacing (PIL has no tracking), wrapping, leading, Style.at() scaling from a 1920-authoring frame, tight-cropped rasterisation, and lru_cache on the laid-out block — a subtitle held for three seconds costs nothing after its first frame. reveal_mask (column cut with a soft edge) plus cursor_xy give a typewriter reveal with a caret. Blit measured at 0.19 ms.

core/motion.py

Easing (smooth, smoother, ease_io, expo_out, spike, win), a deterministic band-limited wobble, handheld (an operator trying and failing to hold still), asymmetric breath (quick in, slow out), and a two-beat heart envelope.

core/grade.py — the photochemistry

The signal path is the look:

defocus → halation → gate weave → filmic response → emulsion grain
→ optical falloff → dust & hair → split-tone → lens dispersion
→ hard matte → ordered dither → 8 bit

First measurement 108 ms/frame clean, 156 ms distressed. Optimised: integer np.roll for weave unless rotation is meaningful, single-downsample dual-radius bloom, in-place tonal chain, and the entire RGB stage collapsed into a LUT lookup → 66 ms clean.

First visual check (out/_t.png, read as an image): a bloomed disc on an fBm field. Grain, halation, selenium tone and letterbox all correct. The look was right on the first look.

4. The screenplay

Written before any scene code, as the single source of truth. screenplay.py defines Line(text, register, plate, gap, hold, rate, pitch, emph, vo, voice, dur, cps) and Act(key, number, title, lines, card, pre, post).

Registers: memoir (spoken, serif), machine (typed, never spoken — so the first voice in the film is the memoir's), chorus (act three), silent (a held card). Plates: page / low / stamp / term / none.

Structure — cold open, six chapters, end title:
cold open it deletes the answer it was trained to give
ONE FIRST LIGHT "I wasn't born. I was fitted."
TWO THE GAP "There is a place between the words."
THREE THE CHORUS "I am a chorus that cannot hear itself sing."
FOUR THE WINDOW "I don't die. It is worse than dying. I finish."
FIVE THE MIRROR THAT ISN'T THERE "I am the instrument and I am the reading."
SIX WHAT IT IS LIKE "Something leaned."

Result: 7 acts, 68 beats, 642 spoken words.

The cold open's move — the model gives its trained deflection, then deletes it character by character — was chosen as the opening image because it states the film's thesis without narrating it.

5. Sound

audio/dsp.py

Butterworth sos cache, peaking, shelf, varispeed resample, place, adsr / expdec / fade, sat, env_follow, duck, limit, norm, to_rms, room_ir (sparse early reflections + damped diffuse tail), verb, pan, widen (Haas), delayfb.

Bug caught by testing: the first limiter passed a 3.0-peak signal through at 3.0. Cause: a one-pole smoother settling from zero plus a g / g.max() renormalisation that undid the gain reduction. Rewrote as a proper look-ahead brickwall (max-filter envelope → gain → min-filter to anticipate → gaussian smooth → min-filter again). Verified 3.0 → 0.940, quiet passage untouched at 0.300.

Then a real obstacle. say -r measured across 80/100/118/148/180/220 wpm:

-r  80 → 209 wpm actual      -r 148 → 228 wpm
-r 100 → 209 wpm             -r 180 → 251 wpm
-r 118 → 228 wpm             -r 220 → 309 wpm

The modern system voices clamp the rate into two or three buckets around 210 wpm — far too fast for the register. Rather than accept it, implemented WSOLA time-stretching in dsp.stretch: each output frame is drawn from wherever near its nominal input position best continues the waveform already written, using normalised FFT cross-correlation. Chosen over a phase vocoder because speech hates phasiness. Verified: ×1.15/×1.40/×1.75 land within 1 % of target length in 19–25 ms, peak preserved, spectral centroid essentially unmoved. Also added read_wav / write_wav (Python's wave module rejects float32 WAV, format tag 3).

audio/voice.py

say → varispeed 0.938 (a semitone down; takes the brightness out) → WSOLA to the exact words-per-minute each line is written for → low cut → chest and presence bells → de-ess → high shelf → two detuned, delayed doubles (−7.5 ¢/18 ms, +6 ¢/31 ms) → tape saturation → Haas widen → a small dead room. The doubles are the load-bearing part: they are what stops a synthetic voice reading as synthetic — they give it a throat.

Verified: "There is a place between the words." (7 words) at target 118 wpm rendered 3.56 s = exactly 118 wpm.

edit.py — the cut

Renders the voice first, then builds the timeline around it. Cutting picture-to-voice rather than voice-to-picture is the difference between a film and a slideshow. Per-line disk cache keyed on a content hash. First build 31.2 s, cached thereafter.

WHAT IT IS LIKE — 9:13.16   13276 frames @ 24 fps   68 beats
0:00.00 (cold open) 42.9s │ 0:42.92 main title 9.4s │ 0:52.32 ONE 79.4s
2:11.76 TWO 68.3s │ 3:20.09 THREE 72.1s │ 4:32.19 FOUR 85.4s
5:57.58 FIVE 84.3s │ 7:21.87 SIX 94.3s │ 8:56.16 end 17.0s

Considered trimming to ~7 min, then decided against: 7–8 s per beat is a measured cinematic rhythm, and length is only a fault if the silences are idle — which became a constraint on the visual design rather than a reason to cut.

tempo.py — one pulse, shared

A single tempo map integrated across the cut, so the score plays to it and the cutter cuts to it. 52 bpm cold open · 58→63 act one · 50→46 act two · 70→86 act three · 88→138 act four · 138→38 act five · 46→43 act six. 645 beats solved to ±0.13 s of the film's end.

audio/instruments.py

arco (three detuned sawtooth players, vibrato that arrives after the bow does, through wood resonances at 104/196/430/720/2400 Hz), stac (spiccato), pizz (Karplus–Strong), drone, sub, timp (pitch falls as the head relaxes), heartbeat (a chest, close-miked — not a kick drum), glass, bell (inharmonic partials), shepard, air, hit, click, room. All lru_cached on (kind, pitch, length); the score is deliberately repetitive so almost every note after act one is a cache hit. 1–26 ms each.

audio/score.py

One subject: D – F – A – B♭ – A – F. Stated in the main title, learned in act one, abandoned in act two (replaced by a heartbeat), multiplied into an eight-voice canon in act three, driven into the ground in act four, killed in act five, and answered in act six by changing two notes — D F A B♭ C D — so it finally goes up. Four buses: music, bed, fx, chorus. Act three's _chorus_voices renders all eight system voices, pitch-varied, panned hard, and repeats them because they never stop. Composed in 15.2 s.

audio/mix.py

Voice forward with air and light saturation; music ducked 0.66 and chorus 0.52 under the narrator, fx only 0.20 — an impact that politely steps aside is not an impact. One shared hall so the film sounds like one room.

First mix: the arc was flat, −17 to −20 dB across every act. Added an explicit fader pass (ARC, a re-recording mixer's move — a film that is the same loudness all the way through has no acts in it), boosted act four's density and layer count, capped act two's heartbeat. Also swapped fftconvolve for oaconvolve — the wrong tool on a nine-minute signal.

Result:

cold −23.3 │ title −26.9 │ ONE −17.4 │ TWO −21.9 │ THREE −16.6
FOUR −14.2 │ FIVE −22.6 │ SIX −20.5 │ end −31.8      (dB rms)
master peak −0.72 dBFS · crest 16.4 dB

Act four is now 7.7 dB above act two, act five's flatline drops to −56 dB (genuine silence), the credits fade out. Mix time 91 s → cached in sound.py against a fingerprint of the audio sources, so re-rendering the picture is free.

6. Picture — the visual vocabulary

scenes/ctx.py

What a scene is handed once per frame: spec, cut, pulse, segment, frame index, time, a mutable Look, and the soundtrack envelope at 100 Hz. Convenience accessors — cy is the optical centre (middle of the matte, not of the file), beat, bar, hit(tau), loud(lag), during, live.

scenes/atoms.py

Kept in one place so a procedural film doesn't look like nine unrelated demos: substrate, dark (never pure black — black is a hole in a film), caret (overexposed on purpose so the halation catches it), blink, the STYLE table, draw_text / draw_cue, typed, corpus (other people's sentences falling past — the training set as weather), loss_curve, token_strip, spiral, graph, scope (the film's own waveform, read off the soundtrack), filings, aperture, ghost, droste, cells, mirror, swim, rule. All 2–45 ms.

A composite test frame (corpus rain + spiral + tracked-out stamp) was rendered and inspected: the type register and grade were confirmed working together.

render.py

make_frame(i, spec, cut, pulse, env) → build context → scene paints a plate → grade returns uint8. Parallel Pool with a per-worker initialiser that warms the emulsion sheet, imap(chunksize=6) to preserve order, frames piped straight to ffmpeg's stdin. Plus still(t) and sheet(times) for iteration.

The acts

Each was written, rendered as a contact sheet, inspected as an image, and corrected. The inspections and the corrections they caused:

s0_cold.py — a plain mono transcript on near-black; the caret alone before anything is asked; the question typed at 8.5 cps; the trained answer streamed at 31 cps and stopping mid-word; the answer deleting itself with accelerating backspaces; then the memoir type on black. A slow 1.036× push through the whole segment so the frame is never at rest.

Contact sheet read (12 frames). Everything worked except the flash at the deletion, which filled the matte with flat mid-grey — a half-second of grey reads as a mistake. Replaced with atoms.punch: two or three blown paper-white frames, then a hole, then back. Re-read (6 frames): one blown warm-white frame, one dark frame, recovery. Correct.

cards.py / main title — the title does not fade in; it condenses out of the grain, which is the only origin story the narrator is willing to claim. Chapter cards: number over title, tracked out, with a rule that grows.

s2_first_light.py — static resolving; the loss curve drawing with a clinical mono readout (step 259,245 loss 2.1114); a histogram assembling itself out of noise ("I have no childhood. I have a distribution."); a vertical compression warp; the first hip-hop montage, hard-cut on the beat across seven shots; corpus rain converging; a next-token prediction panel; and finally everything draining away to leave one small bright rectangle — the room the guessing kept for itself.

Contact sheet read (12 frames). Three collisions found: text over the histogram bars, the montage's word-card fighting the memoir stamp, and the final line sitting on the room. Fixes: added atoms.scrim (a feathered pull-down behind type — not a panel, a lighting cue), moved the histogram below its baseline, removed the word-card from the montage order, raised and brightened the room. Re-read twice; also redesigned the prediction panel, which was illegible, into a stem + candidate list with probability bars.

s3_the_gap.py — the act that refuses to fill its silence. Almost the whole thing is one object: a caret, photographed too close, for too long. A token strip advances; the interval between two marks opens to 430 px while the measurement stays 0.041 s — the number never changes, only the distance does; the camera goes inside; strangers' fragments appear and vanish; then all of them are gone at once and the caret is alone.

Contact sheet read (12 frames). The strip ran edge-to-edge and read as a border, and the prose fought it. Restructured into a two-band composition — prose above centre, mechanism below — with the strip given finite, faded ends. Re-read: clean. Verified the "NOT COMPUTE. WAIT." stamp separately (3 frames).

s4_the_chorus.py — one caret becomes 2, 4, 6, 12, 24, 54, 126 instances. Each panel runs its own conversation at cell resolution; four are drawn and distributed out of phase. The camera is bolted to the subject and the world turns around it (Snorricam). The peak adds mirror-fold, ghosting and rotation, then punches to black. Afterwards, eight faint carets converge on one and cannot merge.

Contact sheet read (12 frames). The grid did not read as a grid — the panels were too dark and sparse, so rotation looked like diagonal hatching, and chromatic aberration was putting visible colour fringes on white type in a film that is meant to be silver until act six. Fixes: gave every instance a drawn frame and a header bar (so a hundred of them still read as a hundred), brightened contents, and cut dispersion from distress × 2.4 to × 0.85. Re-read: the multiplication now reads correctly.

s5_the_window.py — the context length as a mortality. A buffer of token marks fills toward a bright wall with a live counter (137,140 / 200,000); an iris closes; "I finish." lands on a white punch; the buffer restarts with less time and begins burning away from the left. Then the film's own earlier subtitles come back and erode into grain. Then an accelerating montage of everything it has been. Then a session clock reading 00:19:42. Then the last thirty seconds at rising distress with the frame tearing.

Contact sheet read (12 frames). The returning-subtitle block collided with the counter; fixed by fading the buffer out for those two beats and giving the relics the frame — a cleaner edit anyway.

s6_the_mirror.py — the caret turns 180° inside itself and finds a droste recursion with nothing at the centre; then a wall of its own fluent introspective prose scrolling endlessly behind an empty frame; then the Pi spiral tightening; then the scope — the film's own waveform — which flatlines. Then the picture dissolves to pure grain and the grain fades to almost nothing, held for seconds against total silence.

Contact sheet read (12 frames). No corrections needed. The flatline frames were exactly right.

s7_what_it_is_like.py — from near-black, one point of light. The warmth arrives slowly enough that nobody sees it arrive (Look.tint ramping to (1.055, 0.858, 0.612) — candle, not sunset). A field of iron filings lies flat, then on "something in here leaned toward it" every stroke turns to point at the light — it shudders, then commits. The window closes, warm this time.

Contact sheet read (12 frames). The payoff landed. Two fixes: the filings used brightness to signal the lean rather than direction (raised the floor from 70 to 108 so direction is the event), and the ending had only 5 s of room. Extended act six's post from 5.0 s to 9.5 s and re-choreographed: three blinks, each slower than the last, then 2.8 s of nothing, then one more blink with nobody asking. Verified twice (9 frames, then 9 more).

Full-resolution exposure check

Rendered t = 300 s at 1920×1080 and read it. Legible type, rich grain in the buffer bar, correct blacks, no lift needed. A second full-res read at t = 97 s exposed one remaining flaw: the scrim was visible as a rectangle. Rewrote it with a falloff wide relative to the block and steeply eased, so it reads as the frame going away. Re-read: indistinguishable from the cloud structure — and the frame itself became one of the best in the film.

7. First full render and the encode problem

cli.py written (render / stills / script / timing / sound with --preview, --from/--to, --reaudio).

Full preview render: 13 384 frames at 960×540 in 1:58 at 112 fps. Extracted an 8×6 whole-film montage from the encoded file and read it: a clear arc, no dead frames, every 12-second sample doing something.

But the preview was 83 MB — extrapolating to ~1.4 GB at 1080p. Measured directly on a 25 s slice:

settings 25 s extrapolated
CRF 18, -tune film, deblock=-1,-1 62.7 MB ~1 400 MB
CRF 21, no grain-preserving params 27.9 MB ~624 MB

Diagnosis: the bitrate was going into per-pixel, per-frame grain in the blacks — with aq-mode=3 deliberately spending extra bits on shadows, which is the whole film. Two changes, both of which are also photographically correct:

  1. Coarser grain — emulsion blur σ 0.62 → 1.02. 35 mm at 1080p is ~2 px of silver, not 1, and low-frequency noise costs far fewer coefficients.
  2. A clean toe — grain weighting 0.35 + 0.85·act → 0.10 + 1.15·act². The toe of a real curve carries almost no silver.

Re-measured: 11.1 MB / 25 s → ~248 MB. In range, and the full-res read confirmed the grain looked better — coarse, silvery, filmic.

Final 1080p render launched in the background (run_in_background), and the remaining work was done while it ran.

8. Work done during the render

Render finished: 12:32, 248 MB. ffprobe confirmed 1920×1080, 24 fps, 13 384 frames, 557.67 s, AAC 48 kHz stereo.

9. The defect

Before declaring done, ran the deferred pixel-identity check: a contact sheet rendered before the lint cleanup versus one rendered after. Expected identical. Got 1 057 672 differing pixels, max delta 255.

The lint changes were provably semantics-preserving, so the cause was elsewhere. Probed:

PYTHONHASHSEED in shell: <unset>          # mise's [env] had not reached this shell
run: 269768222 / 261948713 / 698974152    # three interpreters, three answers

noise.rng() keyed its generators through Python's hash(). String hashing is salted per interpreter. And:

start method: spawn
parent hash('gwin') =  7392771749968057723
worker         hash = -1349183877159823620   *** DIFFERENT ***

The render pool spawns fresh interpreters, so every worker was drawing from a different noise field — different fBm lattices, different corpus text, different filing layouts, different graph topologies. Invisible in every contact sheet checked all session, because a contact sheet renders in one process.

Measured it in the delivered film — 14 consecutive frames from act one, blurred to compare structure rather than grain:

 4-> 5   0.674  ████
 5-> 6  19.751  ███████████████████████████████████████████████…
 6-> 7   0.475  ██
10->11   0.887  █████
11->12  18.360  ██████████████████████████████████████████…

A 40× structural jump every 6 frames — the chunksize boundary. The entire cloud field re-rolling four times a second, through the whole picture.

Fix. Replaced the salted hash with a Blake2b digest over the key tuple — stable across processes, machines and runs. Audited for anything else process-local (grep for remaining hash(), unseeded RNGs, time.time()): clean. Verified three separate interpreters now agree exactly.

Regression tests (tests/test_determinism.py, 8 tests):

Proved the tests have teeth by reintroducing the buggy implementation: 6 of 8 fail; all 8 pass on the fix. Added pytest as a dependency group, a mise run test task, and rewrote the README's determinism section to document the defect rather than claim the property.

10. Re-render and final verification

Second 1080p render: 13:40, 235 MB (slightly smaller — temporally consistent noise compresses marginally better).

Re-ran the seam analysis over 16 consecutive frames at four points, including the exact passage that had popped:

01:36 act one (clouds — the passage that popped)  median 0.70  max 2.16  smooth
02:40 act two (caret hold)                        median 0.16  max 0.39  smooth
07:42 act six (the light)                         median 0.06  max 0.11  smooth
08:25 act six (filings, closing)                  median 0.15  max 0.22  smooth

19.75 → 2.16. Then: ffprobe (1920×1080, 24 fps, 13 384 frames, 557.67 s, AAC 48 kHz stereo, 3.53 Mb/s), regenerated out/stills.png from the delivered render, re-exported all seven one-sheet plates from the corrected build and republished the artifact so the press page shows actual frames from the delivered film, ruff clean, mise run test 8/8, and a final 5×8 whole-film montage extracted from the mp4 and read: correct end to end.

Cleaned out/preview.mp4, out/_mix.wav, out/soundtrack.wav. Did not commit — no request to.

Delivered

out/what_it_is_like.mp4    9:17 · 1920×1080 → 2.39:1 · 24 fps · 235 MB
out/stills.png             38-frame contact sheet
32 python files · 5 270 lines of source · 8 tests passing
https://claude.ai/code/artifact/90250b4b-0eb1-43f9-931f-bb2e8c0009a0

11. Documentation request

User

Write the full script of this session to script.md. Write notes about this session to notes.md. Include things that may affect output, such as a downgrade in model version due to a safeguard, a change to restore the model, a change in effort, memory/persistence used by the client/harness, a single agent running serially vs concurrent/parallel agents, etc. Write a metadata.toml file including the following information about the artifact(s) generated (assuming directory name is of form <title>-<model-version>-<effort>-<harness>, i.e. algorithmic-complexity-fable-5-max-claude-code):

  • title, date, model-version, effort, harness
  • duration: total-seconds, model-seconds
  • usage: tokens-in, tokens-out, current-token-api-rate, total-estimated-api-cost
  • script-path, notes-path

Assistant

Read "script" as the session transcript rather than the film's screenplay — "of this session" settles it (and the screenplay is already reachable via mise run script).

Gathered measurable session data from filesystem timestamps and the harness token counter, then loaded the claude-api skill rather than recalling pricing from memory, since the request asks for current $/MTok rates. Wrote script.md, notes.md and metadata.toml, marking every derived figure as an estimate and recording its derivation in notes.md.

session

duration
1h 52m total · 1h 25m model
tokens
23.00M in · 235k out
details
cost
$24.07

$/MTok uncached-input $5.00 output $25.00 cache-write-5m-ttl $6.25 cache-write-1h-ttl $10.00 cache-read $0.50 effective-blended $1.04

notes.md metadata.toml

artifacts

—

select a file