A Reddit user quietly built one of the more practical prompt architectures I’ve seen this week. It’s a Spanish translation assistant with multiple query modes, regional breakdowns, and a flag system that keeps responses tight and useful. What makes it stand out is not the complexity, but the discipline. Every design decision points toward one thing: giving you the right amount of information for what you actually asked.
TL;DR: A structured multi-mode prompt turns your LLM into a context-aware Spanish reference tool with regional variant output, etymology deep dives, and clean flag-based control over response depth.
How the Prompt Works
The prompt by u/locanse runs on a simple flag system. You know which mode you need, you prefix accordingly, and the model responds at the right depth. Four modes total:
- 🔍 Basic mode (no flag): Look up any word or phrase and get translations for neutral Spanish, Spain, Mexico, and other common regional variants. Output is capped at 200 words to keep things fast. This is the default for quick reference, the equivalent of pulling up a dictionary tab without the clutter of ads and unrelated definitions. You get what you need and move on.
- Deep mode (
deep:): Full verbose breakdown with etymology, country-level variants, and linguistic context. For when you actually need to understand a word, not just translate it. If you’re trying to figure out why a word shifted meaning between Spain and Argentina, or where a slang term actually originated, this is where you go. The response is intentionally longer and more layered because the question demands it. - Wide mode (
wide:): Open-ended questions about the Spanish language. No single word required. Best for broader grammar or usage questions, especially when web search is available. Think questions like “when do native speakers actually use the subjunctive in casual speech” versus a textbook rule. This mode handles the gray areas that a lookup tool typically can’t touch. - Multiple mode (
multiple:): Same output as basic mode but for several terms at once, separated by line breaks. Useful when you’re reviewing a piece of content and flagged ten unfamiliar words, or when you’re building a glossary and need to batch-process vocabulary quickly instead of running ten separate queries.
There is also a cont: flag that signals the LLM you are continuing from a prior response. The prompt is built for one-off lookups, so long conversations can drift. Context windows accumulate noise. This flag helps manage follow-ups without restarting the whole system from scratch, which matters when you’re mid-session and don’t want to lose the thread of what you were researching.
A few other rules baked in: tiered source lists for slang definitions (especially useful for Mexican slang, where standard dictionaries are notoriously unreliable), automatic spelling and grammar correction on your input so typos don’t break the lookup, and clarification prompts when a query is ambiguous. If a word has two completely different meanings depending on context, the model asks before guessing.
The author runs this with Mistral Large 3 at temperature 0.0. That is a deliberate call. For language reference work, you want deterministic factual output, not creative variation. The same query run five times should return the same answer. If you’re using this for professional translation or content work, consistency matters more than novelty. Any capable model works here, but lock the temperature down regardless of which one you use.
Use Cases
- Spanish learners who want regional context, not just a single translation that may not match what they actually heard. The difference between how a word lands in Madrid versus Mexico City versus Buenos Aires is real, and a generic translation erases that entirely.
- Content creators writing for Spanish-speaking audiences across multiple markets. Spain versus Mexico versus Latin America is a real distinction that affects tone, word choice, and how native speakers receive your writing. Getting this wrong reads as careless to the audience you’re trying to reach.
- Translators and localization professionals who need fast reference with cultural nuance built in, without bouncing between five different browser tabs and cross-referencing regional dictionaries manually.
- Anyone who has Googled Mexican slang and gotten a completely wrong answer from a standard dictionary, or worse, confidently used a word that means something very different in the region you were targeting.
📖 Prompt of the Day
Full prompt is available here: https://pastebin.com/bhgqFRRz
The design principle worth taking: multi-mode prompts with explicit flags let you pull different depths of response from the same system prompt without rewriting anything. You define the modes once, then control them with simple prefixes at query time. The same architecture works for any domain where you need both quick lookups and deep dives from one tool. Legal research, medical terminology, cooking techniques, historical events. Anywhere the depth of the answer should vary based on what you’re actually trying to do, not a fixed format that treats every query the same way.
If you work with any language regularly, this structure ports directly to French, Italian, Portuguese, or any language with meaningful regional variation. The flag system is the reusable part. The Spanish-specific rules (the source tiers for slang, the regional variant list) are just the domain layer. Swap those out and the underlying architecture holds.
Pull it down, run a few queries, and see if the mode structure fits how you actually think about language lookups. If you adapt it for another language, share what you changed. The more domain-specific versions of this that exist, the more useful the original idea becomes for everyone building on top of it.
Frequently Asked Questions
Q: Is this prompt good for learning Spanish?
Yes. The commenter u/DSLAM picked up on this use case, and it seems ideal for learners. You get quick access to regional variants and neutral translations, which helps you understand how words are used in different Spanish-speaking contexts. The basic mode keeps responses concise, so you’re not overwhelmed with info while studying.
Q: What’s the difference between basic mode and deep mode?
Basic mode is fast and focused, it gives you the neutral translation, Spain variant, Mexico variant, and any other regional options in about 200 words. Deep mode goes all-in with lengthy explanations, etymology, historical context, and basically every variant you could imagine. Pick basic for quick lookups (like while reading), deep when you want to really understand a word’s roots and nuances.
Q: How do I provide context when I’m not sure what a word means?
Use the context flag after the word. For example: “valemadrista context: heard on Mexican podcast.” This helps the LLM narrow down the right translation based on how you actually encountered the word.
Q: Can I look up multiple words at the same time?
Yes, use the multiple: flag and put each term on a separate line. You’ll get the same quick, regional-variant output for all of them in one go.
Seeking feedback on Spanish-language translate prompt I use with LLMs
by u/locanse in PromptEngineering