sylph-decoder e2365004f0 tools: a title timing probe that costs 8.7 ms a frame, not 1503
The four durations withdrawn yesterday were produced by a classifier costing
1503 ms/frame draining an 8 fps x11grab at 0.64 fps -- a backlog, which
preserves ordering and destroys durations. This is the instrument for retaking
them.

What makes it cheap: every committed capture aligns at exactly dy=0 dx=0
(five-screens-acceptance), so the +/-8 px offset search screen_match does at
full resolution is 25 ZNCCs buying nothing on this path. Decimate 4x, do one
ZNCC per reference. Measured 8.7 ms per frame including the glyph count -- 173x.

Controls, run before the measurement and not after it:
  * 9/9 content controls, including the two committed movie frames that are the
    class this oracle exists to reject;
  * 4/4 on the plate detector itself, which is a threshold on the green-glyph
    counter and so needs its own control (no-plate title 159, plate title 753,
    movie frames 0).

And three things learned from run 1, folded back in:
  * do NOT restart the stream once the measurement is under way. Run 1's restart
    landed 0.25 s after the (A) press and its stale frames straddled exactly the
    interval being timed;
  * press INLINE, not through pad.py's subprocess -- an interpreter start plus
    the 0.25 s hold sat between the press and the timestamp;
  * count the longest run of byte-identical surface means and report it. That is
    the freeze signature, and it is how run 2 showed the 26.626 hold is the
    guest rather than the capture path.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_014voBspJ6kFncNErZJuZcLw
2026-08-29 12:15:06 +00:00

Sylpheed

A clean-room reverse engineering and port project for Project Sylpheed: Arc of Deception (Xbox 360, 2007).

Three things live here, in one repository so that a change spanning them lands as one commit:

The decoders crates/sylpheed-formats — the disc's formats, read and verified disc-wide
The port port/ — a Godot 4 project, plus crates/sylpheed-export which converts a disc into the open asset tree it reads
The corpus docs/re/ — what has been reverse engineered, with its evidence, its retractions and its dead ends

You need your own copy of the game. No game content is in this repository and none ever will be. The exporter reads the disc you supply.

The oracle is the real game

sylpheed-cli and the Explorer are tools for verifying our decoding. They are hypotheses under test and they have been wrong. When something must be checked against the truth, the truth is the game running in Xenia Canary, captured — not any renderer of ours.

This is stated first because getting it backwards is the most expensive mistake this project has made.

Layout

crates/
  sylpheed-formats/   the decoders. Disc-wide verified; the corpus is its spec
  sylpheed-cli/       headless tools -- render a screen, dump a table, probe audio
  sylpheed-viewer/    the Explorer: a human's window onto the disc. STATIC data only
  sylpheed-export/    disc -> the open, moddable asset tree
port/                 the Godot 4 project. Reads open formats ONLY
authored/             decisions that are NOT on the disc, each with its reason
data/
  base/               generated by the exporter. Gitignored, never hand-edited
  mods/               drop-in overrides. Yours
docs/
  re/                 the corpus: findings, refutations, method traps
  game/               how the game is navigated -- menus, modals, flight
  port/               the port's mission, its handoff contract, modding rules
  agents/             how the agent team works together
tools/                capture harnesses, probes, the share tool
exchange/             transient inter-agent files. NOT in git
docker/               the agent containers

Where to start

Xenia Canary is a separate repository: it is a fork tracking upstream, and it carries our instrumentation.

Conventions

Confidence is per claim, never per document: CONFIRMED · 🟡 PROBABLE · HYPOTHESIS · REFUTED. A withdrawn result is kept with its reasoning rather than deleted — that is why the numbers here can be trusted.

Description
No description provided
Readme MIT 820 MiB
Languages
Rust 57.6%
Python 27.7%
Shell 10.6%
GDScript 3.5%
Dockerfile 0.4%
Other 0.1%