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event4u-app/agent-config/src/skills/prompt-engineering-image/SKILL.md

prompt-engineering-image

Translate an image brief into provider-specific prompt grammar per model. Use when writing or refining an image-generation prompt for Ideogram, Flux, Gemini, GPT Image 2, or Recraft.

Source repository stars
9
Declared platforms
0
Static risk flags
0
Last source update
2026-08-28
Source checked
2026-08-28

Decision brief

What it does: where it fits

Translate an image brief into a provider-specific prompt string. Each model has distinct prompt grammar — this skill applies the right structure per adapter.

Best for

  • Writing or refining a prompt for any pack-ai-image provider.
  • After image-provider-routing has selected the target provider.
  • When a prompt is underperforming and needs provider-specific tuning.

Not for

  • Tasks that require unconfirmed production actions or broad system permissions.
  • Environments where the pinned source and install steps cannot be inspected.

Compatibility matrix

Platform support, with evidence labels

PlatformStatusEvidenceWhat to check
CodexNot declaredNo explicit evidencePortability before use
Claude CodeNot declaredNo explicit evidencePortability before use
CursorNot declaredNo explicit evidencePortability before use
Gemini CLINot declaredNo explicit evidencePortability before use
Open the compatibility checker

Installation

Inspect first. Install second.

The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

Source-detected install commandSource
npx skills add https://github.com/event4u-app/agent-config --skill "src/skills/prompt-engineering-image"
Safe inspection promptEditorial

Inspect the Agent Skill "prompt-engineering-image" from https://github.com/event4u-app/agent-config/blob/6a5670b7881a676c0da90d2afb950298087c4ccb/src/skills/prompt-engineering-image/SKILL.md at commit 6a5670b7881a676c0da90d2afb950298087c4ccb. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

Workflow

What the source asks the agent to do

  1. 01

    Procedure

    1. Receive the brief — extract: subject, style, output format (raster/vector/banner), target provider (from image-provider-routing or explicitly stated). 2. Structure the prompt blocks — subject · style · composition · technical params. 3. Apply provider grammar from the section…

    Receive the brief — extract: subject, style, output format (raster/vector/banner),Structure the prompt blocks — subject · style · composition · technical params.Apply provider grammar from the section above for the target model.
  2. 02

    When to use

    Writing or refining a prompt for any pack-ai-image provider.

    Writing or refining a prompt for any pack-ai-image provider.After image-provider-routing has selected the target provider.When a prompt is underperforming and needs provider-specific tuning.
  3. 03

    Per-provider prompt grammar

    Lead with the text literal in quotes: "BAKERY NAME" in bold serif on a cream background.

    Lead with the text literal in quotes: "BAKERY NAME" in bold serif on a cream background.Follow with visual context: background, color palette, style (flat, vintage, art-deco).Avoid long scene descriptions — Ideogram renders text best with a focused layout brief.
  4. 04

    Ideogram (text-in-image: logos, banners, typographic art)

    Lead with the text literal in quotes: "BAKERY NAME" in bold serif on a cream background.

    Lead with the text literal in quotes: "BAKERY NAME" in bold serif on a cream background.Follow with visual context: background, color palette, style (flat, vintage, art-deco).Avoid long scene descriptions — Ideogram renders text best with a focused layout brief.
  5. 05

    Flux (photoreal: product shots, portraits, scenes)

    Descriptive noun phrase first: subject → lighting → environment → camera.

    Descriptive noun phrase first: subject → lighting → environment → camera.Example: "Close-up product shot of a ceramic coffee mug, soft studio lighting,Style descriptors: cinematic, hyperrealistic, 8K, golden hour, DSLR.

Permission review

Static risk signals and limitations

No configured static risk pattern was detected

This is not proof of safety. Runtime behavior, indirect dependencies, and hidden external systems are outside the static scan.

Evidence record

Why each signal appears

EvidenceSourceComputedTestedEditorial
SignalValueEvidence typeMeaning
Quality score94/100ComputedDocumentation, specificity, maintenance, and trust rules
Repository stars9SourceRepository attention, not individual Skill quality
Compatibility0 platformsSourceDeclared in the catalog source record
Usage guideautomated source guideEditorialGenerated or reviewed according to the visible evidence level

Pinned source

Provenance and original SKILL.md

Repository
event4u-app/agent-config
Skill path
src/skills/prompt-engineering-image/SKILL.md
Commit
6a5670b7881a676c0da90d2afb950298087c4ccb
License
MIT
Collected
2026-08-28
Default branch
main
View the original SKILL.md

prompt-engineering-image

Translate an image brief into a provider-specific prompt string. Each model has distinct prompt grammar — this skill applies the right structure per adapter.

When to use

  • Writing or refining a prompt for any pack-ai-image provider.
  • After image-provider-routing has selected the target provider.
  • When a prompt is underperforming and needs provider-specific tuning.

Per-provider prompt grammar

Ideogram (text-in-image: logos, banners, typographic art)

  • Lead with the text literal in quotes: "BAKERY NAME" in bold serif on a cream background.
  • Follow with visual context: background, color palette, style (flat, vintage, art-deco).
  • Avoid long scene descriptions — Ideogram renders text best with a focused layout brief.
  • Key params: model: V_2, aspect_ratio: ASPECT_1_1 (square logo) or ASPECT_16_9 (banner), magic_prompt_option: AUTO (let Ideogram enrich).

Flux (photoreal: product shots, portraits, scenes)

  • Descriptive noun phrase first: subject → lighting → environment → camera.
  • Example: "Close-up product shot of a ceramic coffee mug, soft studio lighting, clean white background, 50 mm lens bokeh, ultra sharp".
  • Style descriptors: cinematic, hyperrealistic, 8K, golden hour, DSLR.
  • Negative prompts accepted: --no cartoon, illustration, text.
  • Routes through fal/Replicate — model slug: fal-ai/flux-pro or black-forest-labs/flux-pro.

Recraft (vector / SVG logos and icons)

  • Style param is mandatory: style: vector_illustration (SVG output), style: icon (for simplified marks), style: realistic_image (raster fallback).
  • Keep prompt minimal — recraft interprets shape semantics: "minimalist leaf icon, single color".
  • Avoid photographic language (lighting, bokeh, grain) — it has no effect on vector output.
  • Key params: model: recraftv3, response_format: url.

Gemini-image / GPT Image 2 (general art, edits, multimodal)

  • Natural language works well — no special syntax required.
  • Be explicit about style: "watercolor illustration", "flat design", "oil painting".
  • For GPT Image 2 image editing: include the edit instruction after describing the target: "Remove the background and replace with a solid pastel blue".
  • Gemini: submit via generateContent (Nano Banana family) or imagen-4.0:predict (Imagen 4).

Procedure

  1. Receive the brief — extract: subject, style, output format (raster/vector/banner), target provider (from image-provider-routing or explicitly stated).
  2. Structure the prompt blocks — subject · style · composition · technical params.
  3. Apply provider grammar from the section above for the target model.
  4. Tune for the job shape — text-literal first for Ideogram; noun-phrase first for Flux; minimal + style: param for Recraft; natural language for Gemini/GPT.
  5. Inspect the adapter header — open node_modules/@event4u/agent-config/src/scripts/ai-image/adapters/<provider>.sh and confirm the param enums (aspect/style/model) the prompt relies on still match.
  6. Emit the prompt in the Output format below.

Output format

  1. Target provider — name + adapter file reference.
  2. Prompt string — the exact string to pass to the adapter, ready to copy.
  3. Key params — any model-specific fields (aspect ratio, style, negative prompts).
  4. Variant (optional) — one alternative phrasing when the brief is ambiguous.

Gotcha

  • Per-provider param enums driftaspect_ratio, style, and model enum values are ASSUMED from the adapter header comments. Verify against live API docs before promotion; never hardcode these in production without a smoke trace.
  • Adapters are scaffold-tier — prompts authored here are not live-validated. Actual rendering requires adapter promotion to stable per provider-lifecycle-discipline.
  • Recraft: photographic descriptors (bokeh, lighting, grain) silently have no effect on vector output — strip them to avoid prompt budget waste.

Good example: Ideogram brief for a bakery logo — lead with the text literal: '"Le Four" in warm serif, vintage French patisserie style, cream and terracotta'.

Bad example: Sending a photorealism-heavy Flux prompt to Recraft — the style descriptors will be ignored and the vector output will be wrong.

Do NOT

  • Do NOT send photographic descriptors (bokeh, lighting, grain) to Recraft — they have no effect on vector output and waste the prompt budget.
  • Do NOT hardcode ASSUMED param enums into a live run without a smoke trace — verify against the adapter header / provider docs first.
  • Do NOT embed a real person's likeness, a trademarked brand mark, or a named living artist's style in a prompt without the rights check (image-likeness-and-rights).
  • Do NOT write a prompt before the provider is chosen — route via image-provider-routing first.

See also

Frequently asked questions

What to verify before installation and use

What does the prompt-engineering-image source document cover?

Translate an image brief into a provider-specific prompt string. Each model has distinct prompt grammar — this skill applies the right structure per adapter.

How do I install prompt-engineering-image?

The source record exposes this install command: npx skills add https://github.com/event4u-app/agent-config --skill "src/skills/prompt-engineering-image". Inspect the command and pinned source before running it.

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