Hate

LilMGenius/paperthin/skills/depth/hate

作者 LilMGenius7d5dc6235990230e45a24a25c527d81701da5458無授權條款收錄於 2026年10月9日更新於 2026年10月9日

Attack a plan, design, or argument like you want it to fail before you commit real effort — return the single load-bearing objection and the cheapest experiment that would prove it matters, not a checklist. User-invoked on purpose: a hate-it reflex always in the agent's reach would bias it toward demolition. Weighs many failure axes but owns the synthesis to one root.

AI 產生的概覽

攻擊計畫或論證,找出唯一的承重異議,以及能驗證它的最低成本實驗。

功能
這個技能接收計畫、設計或論證,刻意攻擊其承重結構,而不是提出改進建議。它找出整個計畫所依賴的假設,從虛假事實、虛構敘事、錯誤類比、依賴尚未出現的結果、資料外洩與統計檢定力等失效面向進行攻擊,再把發現收斂成一個根本異議。它也會給出第一根釘子:對該假設最便宜的否證方式,並以 root 與 first_nail 的形式回傳,而不是清單。
適用情境
在為一個計畫、設計或論證投入真實心力之前使用,適合想要敵意式預演而非鼓勵的場合。它適用於一個致命缺陷比一長串疑慮更重要的決策,也適用於能用低成本早期測試提前排除昂貴方案的情況。
執行需求
不需要指令碼、套件或憑證;這是僅含指示、由使用者主動呼叫的技能。

Refuse to be nice to the plan — return the one objection that could kill it and the cheapest shot that proves it matters.

Goal

hate asks "what would someone who wants this to fail attack first?" (validity). It attacks the whole plan — not one fact or one line, but the load-bearing structure — and collapses the attack to a single root. The highest-value output is never a checklist — it's one objection plus the cheaper experiment hiding inside the elaborate plan.

Workflow

  1. Pin the load-bearing assumption(s) — what must hold for the whole thing to stand.
  2. Attack on whatever axes apply — the general ones first: a load-bearing fact that may be false, confabulation (a post-hoc story treated as ground truth), analogy-mistaken-for-isomorphism (structure assumed to transfer across domains where it doesn't), future-tense suture (the argument leans on a result that doesn't exist yet), and the sharpest — cites a principle but implements its opposite; and for empirical / research plans, leakage (no external ground-truth enters the validation independently) and statistical power / family-wise α (a true hypothesis auto-failing from uncorrected tests; a near-zero-power condition that rubber-stamps regardless of truth).
  3. Collapse the findings to the single root objection — the one whose failure makes the others moot.
  4. Find the first nail — the cheapest falsification of the load-bearing assumption: the check (in time / cost / sample) that could kill it before the expensive program runs.
  5. Return { root, first_nail } — not a list.

Rules

  • Attack, don't improve — improving is a different reflex.
  • Own the synthesis — many axes may fire, but collapse them to the single load-bearing root; return that, never a list.

Verification

Before finishing:

  1. The root is genuinely load-bearing — the plan falls without it.
  2. The first nail is genuinely cheaper than the plan it would pre-empt.

來源與署名

來源:LilMGenius/paperthin位於skills/depth/hate提交7d5dc62

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