Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add AgriciDaniel/claude-prompts --skill prompt-adaptgit clone --depth 1 https://github.com/AgriciDaniel/claude-promptsWrote 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.
[](https://agentmods.dev/skills/agricidaniel/claude-prompts/prompt-adapt)<a href="https://agentmods.dev/skills/agricidaniel/claude-prompts/prompt-adapt"><img src="https://agentmods.dev/badge/skills/agricidaniel/claude-prompts/prompt-adapt/github.svg" alt="Measured on agentmods" height="20"></a>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.
<a href="https://agentmods.dev/skills/agricidaniel/claude-prompts/prompt-adapt"><img src="https://agentmods.dev/badge/skills/agricidaniel/claude-prompts/prompt-adapt.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00097 | $0.00736 |
| Opus 5 | $0.00048 | $0.00368 |
| Sonnet 5 | $0.00019 | $0.00147 |
| Haiku 4.5 | $0.00010 | $0.00074 |
Grade A, and why
prompt-adapt 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.
How it starts
The opening of the file, as written. The whole thing — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prompt Adapter
Convert prompts between AI models while preserving intent and maximizing output quality.
Adaptation Workflow
Step 1: Identify Source and Target
Determine:
- Source model: What model was this prompt written for?
- Target model: What model should it run on?
- Priority: Preserve style fidelity or optimize for target strengths?
Step 2: Analyze Source Prompt
Break down the prompt into components:
- Core subject/action
- Style modifiers
- Technical parameters (model-specific)
- Negative prompts (if any)
- Aspect ratio / dimensions
Step 3: Apply Model Translation Rules
Load {PROMPT_ENGINE_DIR}/references/model-guide.md for detailed rules. Key translations:
Midjourney -> Flux:
- Remove
--ar,--v,--style,--s,--chaosparameters - Expand shorthand into natural language descriptions
- Flux prefers longer, more descriptive prompts
- Remove
::weight syntax, integrate naturally
Midjourney -> DALL-E:
- Remove all
--parameters - Rewrite as clear, direct descriptions
- DALL-E prefers straightforward language over artistic jargon
- Remove negative prompts (DALL-E doesn't support them well)
Flux -> Midjourney:
- Add
--arfor aspect ratio - Add
--v 6.1or appropriate version - Condense long descriptions into key phrases
- Add style parameters (
--style rawfor photorealistic)
Any -> Sora (Video):
- Add camera movement descriptions (pan, zoom, tracking, etc.)
- Add temporal flow ("the scene transitions from... to...")
- Specify duration if possible
- Focus on motion and action over static details
Any -> Leonardo AI:
- Reference specific Leonardo models (Phoenix, Alchemy, etc.)
- Use Leonardo-specific quality tokens
- Adapt negative prompts to Leonardo format
Step 4: Search for Target Model Examples
Find reference prompts in the target model:
python3 {PROMPT_ENGINE_DIR}/scripts/search_prompts.py "SUBJECT" --model TARGET_MODEL --limit 3
Use these as style references for the adaptation.
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.
- 11d ago First seen · 92 lines · 97 tokens per session scan A 448a535f26f9
prompt-adapt is a skill published in the GitHub repository AgriciDaniel/claude-prompts (106 stars, last pushed 5mo ago), licensed MIT. It adds 97 tokens to every session and 736 once invoked, about $0.0005 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.
Other skills, from other repositories
forensic-prompt-compiler
Forensic image-to-prompt compiler for image generation models. Use this skill whenever the user wants to: convert/describe an existing image into a generation prompt, reconstruct a scene as a prompt, generate prompts from reference images for AI image tools (Midjourney, FLUX, Stable Diffusion, DALL-E, or any diffusion…
seedance-prompt
This skill should be used when the user asks to write, improve, translate, compress, or debug a Seedance 2.0 video prompt; mentions T2V, I2V, V2V, R2V, camera direction, prompt quality, or provides reference assets for a production-ready prompt.
minimax-h3-prompting
Guide an idea into a generation-ready MiniMax H3 / Hailuo H3 prompt or diagnose an inspected H3 output. Use for T2VA, I2VA, FL2VA, L2VA, or Ref2VA; text-only PV and kinetic type, Motion Design/MG, packaging and transitions, product/UI/game/MV/title work, localized reality-to-hand-drawn edits, audio/timbre reference…
ai-video-prompt-generator
Generate AI video prompts from clean structured prompt specs, validate prompt specs, run an isolated OpenAI-based prompt generator, and lint prompt outputs for viewpoint, action, reference, dialogue, negative prompt, audio prompt, safety tags, and legacy-contamination failures. Use when producing or repairing…
image-prompt
A skill that turns a vague request into a detailed prompt for generating images, including options for covers, posters, promotional materials, typography, and other visual formats. A prompt is an instruction given to an image-generation system.
seedance-2-5-prompt-director
A skill for writing and improving prompts for Seedance 2.5, a video-generation system. It covers text-to-video, image-to-video, editing, video extension, references, camera movement, green-screen work, sound, and lip sync.