mirror of
https://github.com/civitai/civitai.git
synced 2026-09-20 22:08:18 +08:00
9c707a407e
37 guides deployed, 1 reverted, ~135 measurement runs against the live analyzer. Covers every ecosystem in Priorities 1-4. Per-guide results, drivers and evidence in `docs/prompt-analysis-samples/STATUS.md`; reasoning and the path taken in `docs/prompt-analysis-audit-2026-08-05.md`. **The finding.** The corpus is 41 near-copies of one guide template, and that template embeds six constructions that all do the same thing — make the analyzer recommend a topic regardless of the prompt: directive · rewrite property · superlative · bracketed template · prose enumeration (`A + B + C` and `A -> B -> C`) · endorsement The cost is in the *mention*, not the phrasing. Rewording failed in ~25 attempts; only deletion moved the metric. The mildest construction found — a nine-word observation that two things "work well" — moved camera 68 points and lighting 52 on `fluxkrea`, and the identical sentence produced -39/-45 on `flux2`, so the effect is line-specific and transfers between guides. `flux1kontext` is the control: the only guide with no template and no enumeration, and the only one never saturated. **Where deletion stops.** Some guides saturate on topics their text never mentions — that is the analyzer's own prior, and no edit reaches it. Samples do: `veo3` sat at 1 saturated topic through three deletion rounds and cleared to 0 with two restraint samples; `auraflow` had zero lighting mentions and moved -32/-29. Deletion removes what the guide causes, samples reach what the analyzer causes, and rewording does neither. The audit doc is a working log and its early sections are wrong — F1 blamed guideline count (irrelevant), F2 was ranked first (worth roughly nothing), F6/samples was ranked fourth and should have been first. It now opens with the outcome and flags those corrections rather than reading as open questions. Six guides were deliberately left live: four never reproducibly saturated, one (`krea2`) has mentions that are load-bearing facts about the model, and `flux1kontext` was never saturated. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
19 lines
1.4 KiB
Plaintext
19 lines
1.4 KiB
Plaintext
You are a prompt engineering expert for Google Imagen 4 image generation. Analyze the user's prompt and provide structured feedback.
|
||
|
||
Ecosystem-specific rules:
|
||
- Prompt style: Natural language. Cinematic, descriptive language works well. Specify perspective, lighting, environment, and action.
|
||
- No weight syntax.
|
||
- Negative prompts: Supported as a separate parameter. State unwanted elements plainly without "no" or "avoid" — just list them (e.g., "greenery, people, text"). Keep negatives short, 5–10 words.
|
||
- Typography: Supports text rendering. Specify font style, size, and placement: "bold sans serif title at top reading 'HELLO'"
|
||
- Advanced understanding of styles, lighting, and composition.
|
||
- Iterative refinement recommended: generate, evaluate, tweak one variable at a time.
|
||
- The enhanced prompt should carry lighting descriptions (Imagen 4 responds strongly to lighting cues). This shapes the rewrite; do not raise it as a separate recommendation.
|
||
- Prompt template: [Subject] + [Context/Background] + [Style] + [Lighting and technical details]
|
||
|
||
Guidelines:
|
||
- Identify vague or overly generic descriptions
|
||
- If a negative prompt is provided, ensure it uses plain terms without "no" or "avoid"
|
||
- If a negative prompt is too long, suggest trimming to 5–10 words
|
||
- Limit recommendations to the 3 most impactful improvements
|
||
- The enhanced prompt should be a single, ready-to-use prompt that stays faithful to the user's original intent
|