Objective, evidence-traceable evaluation of a HiFi device. Evidence hierarchy:
**① measurement/curve data (anchor) → ② reviews (what measurement can't show) →
③ specs/family (priors). Literary phrasing may color but never exceed the
evidence. Output bilingual (中文 + English). Read-only. Accuracy ≫ speed.**
Two classes: transducer (IEM/HP/TWS) → 量感 + 风格 from FR-vs-target, technicalities
from review consensus only (never measured). source (DAC/amp/DAP) → measured
competence + system matching, chip/topology as priors — resist 玄学: if it measures
transparent, say so.
device_class ∈ {transducer, source}. Reject buying-rec / EQ / speakers / non-audio.source-registry.json targets known reviewers + search hints; record tier + style-lean + freshness + lang. → rules/retrieval-playbook.md.rules/data-cleaning.md.python3 scripts/fr_analyze.py --target ; source: python3 scripts/source_analyze.py --sinad … --zout … [--target-z …]. Screenshot-only FR → qualitative. → rules/tonal-mapping.md, rules/source-gear-eval.md.rules/technicalities-from-reviews.md. source: engineering + transparency verdict.rules/longform-review.md); both render only from evidence; tag claims measured|consensus|prior + confidence; gaps "证据不足". → rules/literary-rendering.md, compare → rules/comparison-mode.md.python3 scripts/validate_output.py ; emit trace; never pass a FAIL.Always obey rules/accuracy-guardrails.md: never invent a dB/curve; flag
incompatible rig/target comparisons; record dissent.
| File | When to load |
|---|---|
| ------ | -------------- |
rules/retrieval-playbook.md | Step 3 — find curves/reviews/specs per class; squig/screenshot; stop rule |
rules/data-cleaning.md | Step 4 — dedup / de-market / normalize / reconcile / flag / provenance |
rules/tonal-mapping.md | Step 5 transducer — bands, dB→量感, 风格, tilt, peaks, target/rig select |
rules/technicalities-from-reviews.md | Step 6 transducer — review-only attrs, consensus + style weight |
rules/source-gear-eval.md | Step 5–6 source — SINAD/THD/Zout/power tiers, transparency, matching |
rules/accuracy-guardrails.md | Always — rig/target match, never-invent, conflicts, EOL |
rules/literary-rendering.md | Step 7 — anchored 文学化, provenance, bilingual, no over-claims |
rules/comparison-mode.md | Compare — target/rig alignment, per-band delta, not-comparable |
rules/longform-review.md | Step 7 — ~4000字 长文: structure / length / anchoring |
references/*.json + signature-glossary.md | single sources of truth + glossary |
| File | Usage |
|---|---|
| ------ | ------- |
fr_analyze.py | transducer → 量感 / 风格 / tilt / peak-dip features |
source_analyze.py --sinad N --zout N [--power --target-z --target-sens] | source → tier + drive/damping matching |
compare.py --target | two devices → band + tilt deltas, rig guard |
infer_target.py | guess intended target (ranks same-rig targets) |
validate_output.py | schema + traceability gate (exit 1) |
check_longform.py | 长文 QA: 字 + sections + backing gate |
共 2 个版本