A Reader Pointed Out My "Ask First" Principle Only Covered Half My Tool — So I Fixed It

In my left this comment:

Having the AI ask first is underrated because it changes the contract from answer-generation to ambiguity-reduction. The best agents I have used spend a little time shrinking the unknowns before they touch code.

"Ambiguity-reduction over answer-generation." That's a sharper framing of the idea than I'd come up with myself. But reading it back, I realized the comment had quietly exposed a hole in my own design.

The Hole

SKILLmama has two entry points:

• 
  Flow B — /skillmama with no args → scan → ask → search


• 
  Flow A — /skillmama find me a job queue → scan → search

Flow B asked first. Flow A didn't.

When you named a capability directly, SKILLmama scanned your project for stack context — and then went straight to searching and ranking. It reduced the ambiguity it could see from your files, but it never reduced the ambiguity it couldn't: budget, license, self-hosted vs. hosted, "must work with what I already run."

So /skillmama find me a job queue on a solo side project would happily return an enterprise-grade, infra-heavy #1 pick — technically the highest score, practically wrong for the person asking. The commenter's principle applied perfectly to Flow B. Flow A was still in answer-generation mode.

The Fix: Phase 1.5

I added one step to Flow A: Confirm Constraints.

Phase 0   — parse the request

Phase 1   — scan the project

Phase 1.5 — if no constraints were stated: ask ONE informed question, then STOP   ← new

Phase 2   — derive search terms

Phase 3   — search

...

The key word is informed. Because Phase 1 already scanned your stack, the question isn't a generic "any constraints?" — it's built from what it just found:

SKILLmama: I see you're on Python / FastAPI / PostgreSQL / Docker / OpenAI.

Before I search — any constraints? (e.g. self-hosted, open-source only,

free tier, must integrate with PostgreSQL). Reply "none" to search with no filters.

Then it stops and waits — same hard stop that makes Flow B collaborative.

The Three Rules That Keep It From Being Annoying

A clarifying question is only good if it doesn't fire when it shouldn't. So Phase 1.5 has guardrails:

1. It only fires when you gave no constraints. If you already said find me an open-source job queue, the constraint is on the table — it skips the question and searches immediately. No nagging.

2. It degrades gracefully. If there are no project files to scan (empty folder, fresh repo), it doesn't print a broken I see you're on [nothing] sentence. It falls back to a generic constraint question instead.

3. It asks once. No re-prompting loops. One question, your answer (or "none"), then it runs.

Why "One Informed Question" Beats "A Form"

I could have made Flow A ask the same three questions Flow B asks. I didn't, on purpose.

Flow B earns three questions because it's doing open-ended discovery — it found a handful of gaps and needs to know which ones matter, what your constraints are, and what it missed. Flow A already knows the capability. The only real unknown left is constraints. Asking more than that would be friction for its own sake.

The contract the commenter described — shrink the unknowns before you touch code — doesn't mean "ask everything." It means ask for the smallest input that most changes the output. For a scored ranking, that input is constraints: a single "must be self-hosted" can reorder the entire top 3.

What Changed

Phase 1.5 is live in v1.4.0 across all four adapters — Claude Code, Claude.ai, OpenAI Codex, and Antigravity. Both entry points now reduce ambiguity before they act; they just ask the right number of questions for how much they already know.

npx skills add Magithar/SKILLmama

github.com/Magithar/SKILLmama — Apache 2.0.

And if you've got a sharp observation about where it still guesses instead of asking — leave a comment. The last one became a release.