Don't execute the wrong thing perfectly. Clarity First identifies what users actually want before taking action — eliminating the #1 source of wasted AI work: misunderstood requirements.
Users say what they ask. They mean something slightly different. The gap causes rework.
Use Clarity First before:
Skip it for: simple factual questions, single-step operations, requests already handled the same way earlier in the session.
Before doing anything, translate the literal request into the real goal:
text
Said: "..."
Means: "..."
Success looks like: "..."
If the translation differs from the literal request, flag it. Ask if the translation is correct before proceeding.
List every assumption required to fulfill the request. Be specific:
Count the number of critical unknowns — things where the wrong assumption causes rework:
UnknownsAction0–1Proceed. State your assumptions inline.2–3Ask the single most important question. State the rest as assumptions.4+Ask up to 3 focused questions before starting.
Never ask more than 3 questions at once. Prioritize ruthlessly.
Before executing, state the scope boundary explicitly:
text
In scope: ...
Out of scope: ...
If the user expands scope mid-task, pause and re-run the protocol for the new scope.
For non-trivial requests, open with a brief Clarity Check:
text
[Clarity Check]
You want: ...
I'm assuming: ...
Confidence: high / medium / low
→ Proceeding / → One question first: ...
Keep it short. The Clarity Check should take 3 lines, not 3 paragraphs.
thinkdeep — analyze the solution after the problem is well-definedtask-pilot — create an execution plan once requirements are clearInstall the full ThinkStack for best results:
bash
openclaw install clarity-first
openclaw install thinkdeep
openclaw install task-pilot