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Use this to account for where AI-assisted attention actually went and what it bought - including the uncomfortable parts.
デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。
インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
npx skills add https://github.com/YannisKiefer/the-ai-diary --skill attention-ledgerコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
ローカルで確認しますか？SkillsMP が現在取得できるファイルをダウンロードできます。
Use this as the always-on brain for any question about how someone thinks, decides, debugs, or works with AI. Read the request, find the first match, act.
Use this to test decision patterns against repeated behavioral evidence - without ever labeling from one anecdote.
Use this when analysis is complete. Mine for findings the subject cannot see from inside any single session.
SKILL.md を表示中
| name | attention-ledger |
| description | Use this to account for where AI-assisted attention actually went and what it bought - including the uncomfortable parts. |
Classify episodes approximately into:
PRODUCT VALUE / MAINTENANCE / LEARNING / RESEARCH / INFRASTRUCTURE / AGENT-META WORK / ADMINISTRATION / REWORK
Estimate two shares per class: share of sessions and share of downstream outcomes. The gaps between those two columns are the finding.
Name work that FEELS high-leverage but historically produced little downstream benefit. Name low-visibility work with unusually high leverage. This section should be evidence-driven and possibly uncomfortable.
EXPLORE: alternatives, technologies, architectures, models, strategies. EXPLOIT: commit, implement, ship, polish, scale.
Measure mode switching. Hunt for:
Do not call exploration waste unless outcome evidence supports it. Exploration is R&D until proven otherwise.
Compare deliberation depth against reversibility and downside:
| Decision type | Observed deliberation | Appropriate? |
|---|---|---|
| cheap + reversible | hours of comparison? | over-deliberation |
| expensive + irreversible | minutes? | under-deliberation |
Find both rows in the real data.
Never equate messages, code volume, commits, tokens, or session length with productivity. Use completions, regressions, correction loops, rework, deployment success, later reversals, maintenance burden. State cycle-time uncertainty honestly.
Attention follows interest. Audit whether value followed.