f16 ingratitude-forgiveness

f16 ingratitude-forgiveness is a skill for Claude Code, Codex from ace3000chao/book2startup. It costs 127 tokens per session (2,572 once invoked), scanned A, original, MIT.

A relationship-reflection framework for remembering other people's help, learning from your own mistakes, and letting go of resentment over their wrongs.

In plain words
What is it for?
It helps review friendships, partnerships, and close relationships after conflict or when old resentment keeps returning.
Why use it?
It reduces the burden of keeping score over your own sacrifices and repeatedly revisiting injuries caused by others.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It helps review friendships, partnerships, and close relationships after conflict or when old resentment keeps returning.

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Install with agentmods
npx agentmods add skills/ace3000chao/book2startup/f16
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add ace3000chao/book2startup --skill f16
Clone the repo
git clone --depth 1 https://github.com/ace3000chao/book2startup

Made for: Claude Code, Codex.

Wrote this? Show the measurements

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README.md
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Your own site
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Per session 127 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,572 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00127 $0.02572
Opus 5 $0.00063 $0.01286
Sonnet 5 $0.00025 $0.00514
Haiku 4.5 $0.00013 $0.00257

Measured 9d ago against content hash 0f377db376d3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

f16 ingratitude-forgiveness scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

菜根谭skills/skills/f16/SKILL.md · 139 lines

How it starts

The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.

忘功念过 忘怨记恩框架

R — 原文 (Reading)

"我有功于人不可念,而过则不可不念;人有恩于我不可忘,而怨则不可不忘。"

— 洪应明, 菜根谭·忘功念过 忘怨记恩


I — 方法论骨架 (Interpretation)

不对称记账——对自己的付出记少,对别人的恩惠记多。

这个框架提供了一种人际恩怨的"记账原则":

  1. 我付出了,不要记:你对别人好,不要念念不忘,否则这个"恩"会变成你期待回报的筹码。
  2. 我有过失,必须记:你伤害了别人,不要假装没发生,要记住并承担责任。
  3. 别人对我有恩,记住:别人帮助了你,要记住并感恩,不要把别人的好当成理所当然。
  4. 别人对我有怨,忘掉:别人伤害了你,不要记仇,让它过去,否则你的内心会被怨恨填满。

核心逻辑:

  • 对自己:严格——功少记,过多记。
  • 对别人:宽松——恩多记,怨少记。
  • 这不是道德要求,而是"让自己内心更轻松"的策略——记太多怨恨会让你成为囚徒。

一句话总结: 记住该记住的,忘掉该忘掉的。


A1 — 书中的应用 (Past Application)

案例 1: 诸葛亮的"忘功"

  • 问题: 诸葛亮一生为蜀汉鞠躬尽瘁,辅佐刘备、刘禅两代,功勋卓著。但他从未"念功"——他从未以"我对蜀汉有功"来要求特殊待遇或回报。
  • 方法论的使用: 诸葛亮在《出师表》中说的是"此臣所以报先帝而忠陛下之职分也"——他说的是"报恩",不是"记功"。他把自己的一切付出定义为"应该做的",不是"需要被记住的"。
  • 结论: "忘功"不是否定自己的付出,而是"不把付出变成期待回报的筹码"。
  • 结果: 诸葛亮死后,蜀汉百姓追思,千古流芳。"忘功"的人,反而被历史记住。

案例 2: 舜的"忘怨"

  • 问题: 舜的父亲和弟弟多次想害他(父亲瞽叟和弟弟象合谋想烧死舜、让舜挖井时活埋舜)。
  • 方法论的使用: 舜没有"念怨"——他没有记住这些伤害,没有在后来进行报复,反而继续孝顺父亲、友爱弟弟。当尧问谁可以继承天下时,舜没有说"我比弟弟强",而是让弟弟继续得到任用。
  • 结论: "忘怨"不是软弱,而是"不让怨恨成为自己的枷锁"。
  • 结果: 舜成为中华文化的道德楷模,成为"二十四孝"之首,继承了尧的帝位。

A2 — 触发场景 (Future Trigger) ★

用户会在什么情境下需要这个 skill?

  1. 长期积累的怨恨需要释放:用户对某人的怨恨已经累积很久,每一次想起来都觉得痛苦,想知道"我该如何处理这份怨恨"。
  2. 在关系中评估"谁付出更多":用户觉得自己付出很多但对方不领情,想知道"我的付出是否变成了筹码"。
  3. 人际冲突后的修复:用户和某人发生了冲突,事后想修复关系但不知道该怎么处理恩怨。
  4. 想放下但放不下:用户知道应该"算了",但心里过不去,想找一个框架来真正"放下"。
  5. 评估自己的"记账方式"是否健康:用户想知道自己的人际恩怨观是否正常,是否过度记仇或过度记恩。

语言信号 (用户的话里出现这些就应激活)

  • "我对他这么好他却这样对我"
  • "为什么我总是记得别人对我的伤害"
  • "我放不下"
  • "他欠我的"
  • "我不想原谅他"
  • "我帮他这么多,他却..."
  • "每次想到那件事我就难受"
  • "我该记仇还是算了"

与相邻 skill 的区分

  • f08(推己及人对治换位框架) 的区别:f08 是"通过换位推演来理解对方,从而化解对他的苛责";f16 是"通过不对称记账来让自己内心更轻松"。f08是理解,f16是放下。
  • f12(一念转魔成佛框架) 的区别:f12 是"在情绪即将失控的瞬间如何转念";f16 是"在事后如何处理累积的恩怨"。f12是危机处理,f16是长期心理调适。

E — 可执行步骤 (Execution)

当 skill 被激活后, agent应按以下步骤执行:

  1. 确认当前的"怨恨"或"不甘"

    • 完成标准: 明确说出"你对谁有怨?或谁欠了你什么?"并量化这个"债"的严重程度(1-10)。
    • 判停条件: 若用户只是泛泛的"我对很多人都有怨",则要求其具体化到"一个人、一件事"。
  2. 执行"不对称记账"检验

    • 完成标准: 问用户四个问题:①"我对他的付出,我还在念吗?"(如果念,说明你的"功"没有忘);②"我伤害过他的地方,我记住了吗?"(如果不记,说明你的"过"没有念);③"他帮过我的地方,我记住了吗?"(如果不记,说明你的"恩"没有记);④"他伤害过我的地方,我还在记吗?"(如果还在记,说明你的"怨"没有忘)。
    • 判停条件: 若用户发现自己"记功忘过、记怨忘恩"(完全相反),则提示"这正是你痛苦的根源——你在用错误的记账方式让自己成为受害者"。

Read the full file on GitHub · 139 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 139 lines · 127 tokens per session scan A 0f377db376d3

Subscribe to this mod's changes

f16 ingratitude-forgiveness is a skill published in the GitHub repository ace3000chao/book2startup (80 stars, last pushed 4mo ago), licensed MIT. It adds 127 tokens to every session and 2,572 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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