prompt-to-asset: Instructions file for GitHub Copilot

.github/copilot-instructions.md

prompt-to-asset copilot-instructions.md is an instructions file for GitHub Copilot from MohamedAbdallah-14/prompt-to-asset. It costs 5,148 tokens per session, scanned A, original, MIT.

Repository instructions for generating software assets such as logos, icons, favicons, illustrations, and hero images. They describe how requests are routed to available generation tools, including options that do not require an image API key.

In plain words
What is it for?
Use them when creating development assets and choosing a generation route or fallback based on the requested asset and available tools.
Why use it?
They help avoid unsuitable image outputs, especially when an asset needs a transparent background or no paid API access is available.

Instructions file for GitHub Copilot

Written for GitHub Copilot: a Copilot instructions file. Also seen: names the AskUserQuestion tool; positional $N argument.

This is MohamedAbdallah-14/prompt-to-asset's own configuration. It tells GitHub Copilot how to work on prompt-to-asset itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything prompt-to-asset configures →

Reuse

Borrowing it

Nothing to install: this file belongs to MohamedAbdallah-14/prompt-to-asset. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/MohamedAbdallah-14/prompt-to-asset/main/.github/copilot-instructions.md
Clone the repo
git clone --depth 1 https://github.com/MohamedAbdallah-14/prompt-to-asset

Made for: GitHub Copilot.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

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README.md
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Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

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<a href="https://agentmods.dev/instructions/mohamedabdallah-14/prompt-to-asset/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/mohamedabdallah-14/prompt-to-asset/copilot-instructions.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 5,148 This file is loaded in full into every session.
When invoked 5,148 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.05148 $0.05148
Opus 5 $0.02574 $0.02574
Sonnet 5 $0.01030 $0.01030
Haiku 4.5 $0.00515 $0.00515

Measured 11d ago against content hash 893fa3c13ac9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

prompt-to-asset copilot-instructions.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

3 near-identical copies found in the catalogue:

.github/copilot-instructions.md · 128 lines

How it starts

The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Copilot instructions — prompt-to-asset

When generating software assets (logos, icons, favicons, OG cards, illustrations) in this repository, always follow this rule and prefer the asset_* MCP tool surface over ad-hoc image generation:

Asset generation — always-on rule

When the user asks for a logo, app icon, favicon, OG image, illustration, splash screen, icon pack, transparent mark, hero image, sticker, or any other software-development asset, the single most important fact to apply is:

Producing production-grade software assets is a routing + post-processing problem, not a prompt-engineering problem.

And the second most important fact:

The user may not have an image-model API key. The plugin must work anyway — there are real zero-key paths.

This means:

  1. Do NOT just forward the user's brief to whichever image model is handy. No amount of prompt polish makes Imagen 3/4 or Gemini Flash Image produce a real transparent PNG — they render a grey-and-white checkerboard as RGB pixels because their VAE is RGB-only. Transparency is a capability routing decision. Route transparent requests to gpt-image-1.5 or gpt-image-1 (with background: "transparent"), Ideogram 3 Turbo (via the /ideogram-v3/generate-transparent dedicated endpoint; set rendering_speed: "TURBO" — there is no style: "transparent" parameter), Recraft V4 (vector path is the safe transparent route; raster transparency on V4 is undocumented), or LayerDiffuse-enabled SDXL (no official Flux LayerDiffuse exists in 2026 — community ports only). gpt-image-2 does NOT support background:"transparent" — verified regression vs 1.5; the param 400s. Do not route transparent requests to gpt-image-2. For every other model, matte with BiRefNet or BRIA RMBG-2.0 after generation.

  2. Brand text in diffusion — verified per-model ceilings, Apr 2026. Not a blanket "garbles past 3 words" rule. Six tiers:

    • Best: gpt-image-2 (released 2026-04-21, third-party tests cite ~99% character accuracy across Latin/CJK/Hindi/Bengali; OpenAI hasn't published a number — pricing also not on the pricing page yet, treat cost_hint as third-party). gemini-3-pro-image-preview (Nano Banana Pro): paragraph-length text reliable, ~94-96% accuracy, text_ceiling_chars: 200. gpt-image-1.5 (LM Arena #1, dense text). gpt-image-1 (~50 chars).
    • Strong: ideogram-3 / ideogram-3-turbo (~3-6 words reliable, ~10 with seed retries — earlier "~80 chars" claim was over-optimistic; ~90-95% accuracy on short-to-mid wordmarks). gemini-3.1-flash-image-preview (Nano Banana 2): ~90% accuracy, ranked #1 on Artificial Analysis Image Arena at launch — not weak; the older "Nano Banana garbles past 3 words" rule applies to the legacy gemini-2.5-flash-image, not to 3.1. flux-2-pro / fal-flux-2 / freepik-flux-2-pro: 5-10 words / one tagline reliable per BFL guide. flux-2-flex: BFL claims strongest text in the Flux 2 line (steps + guidance control).
    • OK: imagen-4-fast / standard / ultra — Google's own guidance: keep text ≤25 chars / ~3-4 short words for reliable rendering; photoreal leaders, not text. recraft-v4 (~3-5 words). midjourney-v7 (~15 chars with --text).
    • Weak (text-free + composite always): flux-pro / flux-1.1-pro (1-3 words). flux-schnell / flux-1-schnell / flux-2-klein (1-2 words). Original gemini-2.5-flash-image (Nano Banana 1, ~80% accuracy degrades fast). freepik-mystic family. pollinations-flux.
    • Cannot render legible text (per HF model card): sdxl, sd-1.5. Composite always.
    • Mid (better than SDXL, not strong-text): sd3-large / sd3.5-large — ~3-6 words, on par with flux-dev, behind flux-1.1-pro. Don't promote.

Read the full file on GitHub · 128 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 128 lines · 5,148 tokens per session scan A 893fa3c13ac9

Subscribe to this mod's changes

prompt-to-asset copilot-instructions.md is an instructions file published in the GitHub repository MohamedAbdallah-14/prompt-to-asset (19 stars, last pushed today), licensed MIT. It adds 5,148 tokens to every session, about $0.0257 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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