Source profileQuality 94/100

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
7
Declared platforms
0
Static risk flags
0
Last source update
2026-07-28
Source checked
2026-07-28

Decision brief

What it does—and 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/0adf49a8ae84b0ff6e2de8759eea43257e020eff/src/skills/prompt-engineering-image/SKILL.md at commit 0adf49a8ae84b0ff6e2de8759eea43257e020eff. 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 stars7SourceRepository 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
0adf49a8ae84b0ff6e2de8759eea43257e020eff
License
MIT
Collected
2026-07-28
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

Alternatives

Compare before choosing

Computed 9438,313

wshobson/agents

brand-landingpage

Brand-first landing page designer — runs a brand-identity interview (colors, typography, shape language), then generates and iterates on a polished landing page via Stitch with deployment-ready HTML. Use when the user asks to create, design, or build a landing page, homepage, or marketing page and has no established visual direction. Skip when they have a design mockup, need a dashboard or app UI, are working at component level, building a multi-page app, or restyling with known design tokens —

Computed 91234,327

affaan-m/ECC

videodb

See, Understand, Act on video and audio. See- ingest from local files, URLs, RTSP/live feeds, or live record desktop; return realtime context and playable stream links. Understand- extract frames, build visual/semantic/temporal indexes, and search moments with timestamps and auto-clips. Act- transcode and normalize (codec, fps, resolution, aspect ratio), perform timeline edits (subtitles, text/image overlays, branding, audio overlays, dubbing, translation), generate media assets (image, audio, v

Computed 91933

dpearson2699/swift-ios-skills

ios-localization

Implement, review, or improve localization and internationalization in iOS/macOS apps — String Catalogs (.xcstrings), generated localizable symbols, stable key naming, LocalizedStringKey, LocalizedStringResource, pluralization, FormatStyle for numbers/dates/measurements, right-to-left layout, Dynamic Type, and locale-aware formatting. Use when adding multi-language support, setting up String Catalogs, enabling generated symbols for compile-time-safe localization keys, handling plural forms, form

Computed 8524,265

openai/skills

figma-implement-design

Translates Figma designs into production-ready application code with 1:1 visual fidelity. Use when implementing UI code from Figma files, when user mentions "implement design", "generate code", "implement component", provides Figma URLs, or asks to build components matching Figma specs. For Figma canvas writes via `use_figma`, use `figma-use`.