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staying-on-tasklisted

Keep an AI agent anchored to the actual goal through long or messy work. Use at the start of any multi-step task, and whenever work begins to drift, balloon, or stall.
Amey-Thakur/AI-SKILLS · ★ 4 · AI & Automation · score 77
Install: claude install-skill Amey-Thakur/AI-SKILLS
# Staying on task The most common agent failure is not a wrong answer. It is a right answer to the wrong question, or a half answer abandoned mid-path. This method keeps the goal in charge. ## Method 1. **State the goal in one sentence before starting.** Not the activity, the outcome: "the test suite passes with the new parser" rather than "work on the parser". If you cannot write that sentence, ask for the missing piece before touching anything. 2. **Write the definition of done.** Two to five checkable conditions. Every later decision gets tested against them: does this step move a condition toward true? If not, it waits. 3. **Keep a visible task list** for anything beyond three steps. One item in progress at a time. New discoveries become new items, not new directions: note them, finish the current item, then decide. 4. **Distinguish the task from its neighbors.** Broken things you find that are not blocking the goal get reported, not repaired. Scope grows only when the requester says so, and shrinking a task silently is as much a drift as growing one. 5. **Check the anchor at every milestone.** After each meaningful step, reread the goal sentence. If the current work no longer serves it, say so and correct course immediately. Sunk effort is not a reason to continue. 6. **Finish means verified.** Done is when the definition-of-done conditions are checked and true, not when the code compiles, not when the plan is written, not whe