docs(reception): reception panel — a pitch debugger, with its controls

[laurigates]

What

A reception panel: agents playing real audience roles reading loractl cold, tuned to r/StableDiffusion. Reframed from the original idea on purpose — this is not a confidence oracle, it is a README/pitch debugger. A simulated reviewer saying "I'd star this" cannot supply confidence, because we wrote the prompt. What it can do well is find where the pitch loses a reader and enumerate what people will demand that the repo cannot supply.

Nothing in crates/ changes. This produces evidence, not code.

Result

NEW=12, KNOWN=1, REFUTED=1 against a pre-registration committed before dispatch (9e33234), on a threshold of 3. Every finding was verified against the real repo before it reached the rollup.

The four that decide reception — all product gaps, not doc gaps:

Gap	Evidence
No mid-training image preview; output.sample_every > 0 is rejected on the diffusion path	diffusion_trainer.rs:325-328
One dataset folder — no per-concept subsets, num_repeats, or regularization images	config.rs:439-441
AdamW only — no optimizer choice, LR schedule, or warmup (ss_optimizer is written as metadata)	config.rs:515-520
Krea 2 is the only target, and ai-toolkit already trains it alongside ~40 models	ai-toolkit/README.md:35

Plus one security-adjacent finding: unauthenticated POST /runs confines output.dir and resume.from, while its own doc comment claims no unvalidated path reaches the trainer — dataset.path and the model.* overrides do (routes.rs:100-124). No ADR covers it.

Seven cheap verified fixes (README says "Three crates" for a four-member workspace, backend list omits candle, precision list omits bf16, presets omit krea2-comfyui, a stale "never executed by any test" comment, a presence-keyed LORACTL_SKIP_GRAD_CHECK, a hand-bumped cache literal) are itemized in the rollup.

Why the controls matter more than the findings

The stated risk was that a panel can be confidently wrong in a way that feels like validation. It happened, and the controls caught it:

• A persona was discarded, mechanically, at a 67% evidence-drop rate. The drive-by asserted ADR content having seen only ADR filenames in a directory listing — and starred the project on that basis. No judgment call was involved; the collator drops findings without a file:line.
• A finding was refuted by measurement. One persona claimed removing dropout from LoraLinear::forward "leaves the whole suite green". Applying that exact mutation fails tests/dropout.rs:117 in 2.37s. It re-asserted the claim on second pass; the mutation outranks it.
• The planted contradiction was caught. The claim auditor's staged README said ~1.8 s/step; it traced that to roadmap.md:314's 4482.18 ms unprompted, so its clean verdict on the real claims is worth something.
• Tier boundaries were enforced as staged directory trees, not as instructions — tier-0/1 personas physically could not read ADRs, the roadmap, CLAUDE.md, or .claude/. Contamination check: zero hits.

"Is this slop?" — answered mechanically, not by opinion

scripts/slop-metrics.sh, deterministic, calibrated against five comparables:

	loractl	ripgrep	bat	sd-scripts	ai-toolkit
test fns / kLOC	10.51	8.81	24.20	1.43	0.08
asserts / test	3.46	4.11	2.15	2.69	2.22
trivial-only tests %	0.25	3.34	1.32	2.42	0.00
non-test unwrap / kLOC	4.10	24.48	7.46	0.14	0.13

Two measurement bugs were found and fixed before any number was quoted, both of which produced plausible wrong answers: os.walk discovery counted stale agent worktrees under .claude/ (full repo copies, ~4x inflation — now git ls-files), and a macro-only assertion regex scored loractl at 9% zero-assertion tests when those were the burn tensor-equality proofs using .assert_approx_eq::<f32>(…) — the same bug scored bat at 52%.

Recommendation

Read docs/reception/2026-08-11/rollup.md §7. Short version: the panel surfaced a venue mismatch that was not among the original four questions. What is strongest here — the architectural invariant, numerics pinned against upstream source, the refusal to publish a misleading cross-tool benchmark — are r/rust virtues. What r/SD evaluates on is four "no"s today. Land the cheap fixes, post to r/rust first, and treat mid-training sampling as the gate for r/StableDiffusion.

Reusable shape

.claude/review-harness.yaml holds everything project-specific (pitch, tier globs, comparables, seed definition, persona roster), so pointing this at the ComfyUI packs or FoundryVTT modules means writing one manifest and changing nothing else. Promotion to claude-plugins skills is deliberately deferred until the shape has survived this one real run — which it now has, with the caveat that the drive-by persona needs a stricter evidence rule before it is trustworthy alone.

Verification

• slop-metrics.sh and collate-reception.sh both byte-identical across two runs
• Competitor citations spot-checked against the cloned trees — all four real
• Contamination grep over tier-0/1 reports — zero hits
• Seeded contradiction caught; mutation test run and reverted (git diff clean)

🤖 Generated with Claude Code

https://claude.ai/code/session_01G2coLedDz1Kv8kfUdb6Rem

[laurigates]

Follow-ups filed as issues so they survive this PR being merged and closed:

• feat(trainer): mid-training image previews on the diffusion path #223 — feat(trainer): mid-training image previews on the diffusion path (the gate before r/StableDiffusion)
• fix(api): POST /runs leaves dataset/model paths unconfined while documenting otherwise #224 — fix(api): POST /runs leaves dataset/model paths unconfined while documenting otherwise

The remaining items — the seven cheap verified fixes, the dataset-subset and optimizer-selection gaps, and the repo cosmetics — are itemized with evidence in docs/reception/2026-08-11/rollup.md §2 and §4. Not filed individually to avoid an issue backlog nobody reads; say the word and I'll split them out.