interview-style-doc-building – Other skill for AI agents

Interview-Style Doc Building

Use this mode when the current user explicitly chooses interview-led authoring; the upstream author's preferences are not facts about every user. AI does NOT propose content — AI asks one question, the user answers, AI patches the file, AI asks the next question. The file IS the conversation's output, updated incrementally.

When to Use

• Building a new SSOT file (life priorities, life vision, principles, frameworks, ranked lists).
• Filling out a structured doc the user explicitly wants to author themselves.
• Quarterly/annual reviews where the user's words go into the file.

NOT for: day planning (use day-plan), task triage (organize-tasks), or anything where AI proposes content first.

The Loop

1. Create the file with a skeleton (header, sections, "to be filled in" placeholders). Use available file tools for a new authorized destination; preserve existing content and use targeted edits afterward. Tool names vary by host.

2. Ask ONE question. Concise. Specific. Single-faceted. Open-ended where possible.

3. Wait for the answer. Don't ask the next question yet.

4. Patch the file with the user's answer in the correct section.

5. Re-ask — next question, or follow-up if the answer was incomplete.

6. Repeat until the file is complete.

Hard Rules

• One question at a time. Never dump multiple questions in a single message. The user has flagged this.
• Patch, don't overwrite. After the initial skeleton, use patch for every update. Never write_file to an existing doc.
• Update the file BEFORE asking the next question. Order: receive answer → patch file → ask next question. Not the reverse.
• Lists from the user are UNORDERED SETS. When the user lists items in response to "which X should we cover?" or "what are the Ys?", that is a SET, not a ranking. Never infer rank, priority, or sequence from the order they typed them. If you need ordering, ask explicitly: "Which of these is #1?"
• Ask dynamics, not names. When the user references a person, don't ask "who is X?" — ask about the role/dynamic.
• No snark, no attitude, no filler. Concise questions, concise acknowledgments.
• No speculative additions. Don't invent sections, edge cases, or "anything else?" prompts unless the user asks.

Question Design

• Domain-discovery, not confirmation. "What wins against everything else?" — not "Is Business #1?"
• Surface new reality. Each question should pull out info AI doesn't already have.
• Engine-move framing where applicable. "What's the thing that, if true, makes the rest obvious?"
• Concrete over abstract. "What's #2 — the domain that wins against everything except #1?" beats "Tell me about your second priority."

File Patching Pattern

After each answer:

1. Read the relevant section (if not already in context).

2. patch with old_string = placeholder or previous entry, new_string = updated content with the user's words preserved.

3. Confirm the diff. Move on.

For ranked lists, append one rank at a time:

1. **Business** — Q2 #1 goal: ...
2. **Health** — get below 81.0 kg, sleep 9h/day, ...

Each rank gets patched in as the user confirms it.

Common Pitfalls

• Assuming order from a set. The user lists "A, B, C, D" → AI writes "1. A, 2. B, 3. C, 4. D" → the user flags it. ALWAYS confirm rank explicitly.
• Asking too many questions at once. Even bundling 2 violates the rule.
• Overwriting the file instead of patching specific sections — destroys prior content.
• Adding AI-generated content to fill out sections. Sections stay empty until the user provides the content.
• Skipping the file update between Q&A pairs — the doc falls out of sync.

Pairing with Other Skills

• day-plan — different pattern (task triage), not interview-style.
• organize-tasks — Todoist-specific.
• memory-management — separate from this; persona/preferences go to memory.

Limitations

• Adapted from davidondrej/skills; verify local paths, tools, credentials, and agent features before acting.
• For commands, remote access, scheduling, browser automation, or file-changing workflows, get explicit user approval and confirm the target environment first.