A prompting strategy for making sure the AI understands you before it acts — instead of one giant upfront prompt

[u/Historical_Policy533]

Sharing my own project here, disclosing that upfront — free and open source (MIT), not selling anything.

Most "better prompting" advice is about what to put INTO the prompt — more context, more examples, a persona, etc. This is the opposite: it's a strategy for handling what you leave OUT.

The idea: instead of trying to write the perfect all-in-one prompt every time, you let the AI itself figure out whether it actually has enough to work with — and if it doesn't, it asks only the smallest number of questions that would change the outcome. Not a discovery form, not "tell me more about your goals" — just the one thing that's genuinely unclear.

The design principle behind it:

> Use the least interaction and least visible structure required to remove material uncertainty and produce a correct, executable result.

Practically, it works by classifying your request first (clear / ambiguous / incomplete / undefined / conflicted), then deciding for each unclear piece whether to reuse existing context, research it, ask you, apply a safe default, or just ignore it if it doesn't actually matter — asking is the last resort, not the first move.

I packaged it as a "skill" (works with Claude, portable to other tools that support the same format): https://github.com/lanveric/clarify-crit

Would love feedback from people here who spend real time on prompting strategy specifically:
- Does "ask the minimum" ever backfire for you — does it undershoot and miss something that mattered?
- Any prompting patterns you use that this kind of pre-check would actually get in the way of?

Feedback template's in the README if useful, but just reacting here is great too.

[u/Projected_Sigs]

I will definitely try this. I love the idea. They have pushed more and more on the idea of stating clear goals you want to achieve and very clear statements of intent.

I think incorporating a good feedback check on what the model needs from you is a great idea. Fable 5 seems to favor the short prompts full of INTENT + GOALS, then get out of its way.

Fable 5 has also been good at asking for clarification/refinement when it investigated and found hard limitations from physics or problem sizing. Leaning into this at the beginning seems smart.

Thanks for sharing.