- FINDINGS.md: dated 2026-06-12 entry logging in-the-wild verbatim
misreads (7/10 exact, ~3.3% per-char, 2/3 silent) alongside flawless
gist-tier recall in the same session. Explicitly anecdotal, n=1,
non-reproducible — motivation only.
- eval/glyph-matrix/PLAN.md: public plan for the paused confusion-matrix
experiment (Task #7) so the pending work is visible outside README,
per the measured-numbers-only README rule.
- ON 47823 / OFF 47824 with own PXPIPE_LOG files: operator session can
never pollute bench measurement (separation by construction)
- resume = skip existing patch files; clean stop on quota errors
- Docker grading documented as proxy-free (no model calls in containers)
- README: mention Pro pilot alongside Lite
- src/dashboard/fragments.ts: server-side HTML fragment renderers reusing the
same JSON payloads (HTML and JSON surfaces can't drift)
- node.ts/dashboard.ts: /fragments/<name> routes (header, session-summary,
recent, latest, sessions, stats, toggle) with htmx polling + Alpine for
local state; toggle is a POST-returning-fragment htmx swap
- vendored htmx 2.0.4 + Alpine 3.14.9 in src/dashboard/vendor.ts (offline,
single-file npm package, no CDN)
- deleted Svelte components/stores/bundle build step; dropped svelte/vite
devDeps; build is now just tsc + esbuild
- tests: +5 fragment contract tests (routing, toggle state, HTML escaping of
source text, 404) - 339 total
- PXPIPE_PROVIDER=cloudflare-ai-gateway + PXPIPE_GATEWAY_BASE_URL derive both
family routes ({base}/anthropic, {base}/openai) from one configurable base
- PXPIPE_GATEWAY_HEADERS injects auth headers (JSON or k=v;k2=v2) on every
upstream request incl. count_tokens probes
- OpenAI paths drop /v1 to match gateway shape; Anthropic paths unchanged;
unknown paths pass through on the family route; streaming untouched
- no hardcoded hostnames; tests use fake gateway URLs/tokens (14 new)
- ImageEntry carries sourceText (capped 64KiB upstream in transform.ts)
- new GET /api/image-source[?id=N] endpoint
- LatestPng gains a 'view source text' toggle so the operator can see
the exact text -> image conversion side by side
Does the model actually read pixelpipe's render, or coast on memorized answers?
- novel random-number problems (un-memorizable): text 100% vs image 93% (-7pp real reading tax)
- GSM8K (in training data): 97% vs 96% -- inflated ~3pp by recall
- verbatim recall from a dense render: 0/15
README 'Benchmarks' section leads with the clean 93% and reports the failure
rows too (no cherry-pick). Harness in eval/gsm8k/: gen_novel.py, render_cfg.mjs
(pixelpipe's real renderTextToPngs), bench.py -- claude -p, exact-match grading.
The runtime kill switch reset to ON on every restart, silently re-enabling
the lossy text->image path (which also broke extended-thinking turns).
Default compressionEnabled to false: off on startup, survives restart;
only an explicit dashboard toggle turns it on.
teamchong