affaan-m/ECC
在回答前，为用户提供关于消耗多少响应深度的知情选择。当用户明确希望控制响应长度、深度或令牌预算时使用此技能。触发条件："token budget", "token count", "token usage", "token limit", "response length", "answer depth", "short version", "brief answer", "detailed answer", "exhaustive answer", "respuesta corta vs larga", "cuántos tokens", "ahorrar tokens", "responde al 50%", "dame la versión corta", "quiero controlar cuánto usas"，或用户明确要求控制答案大小或深度的清晰变体。不触发条件：用户已在当前会话中指定了级别（保持该级别），请求明显是单字答案，或"token"指代认证/会话/支付令牌而非响应大小。
npx skills add https://github.com/affaan-m/ECC --skill "docs/zh-CN/skills/token-budget-advisor"Source checked Jul 28, 2026·Refresh due Oct 26, 2026
Reorganized from the pinned upstream SKILL.md
According to the pinned SKILL.md from affaan-m/ECC: 在Claude回答之前拦截响应流程，让用户选择回答深度。
npx skills add https://github.com/affaan-m/ECC --skill "docs/zh-CN/skills/token-budget-advisor"Best fit
Bring this context
Expected outputs
Key source sections
Sections are extracted automatically from the pinned SKILL.md and link back to the source.
用户希望控制回答的长度或详细程度 用户提及token、预算、深度或回答长度 用户说"简短版"、"太长不看"、"简要"、"25%"、"详尽"等 任何用户希望预先选择深度/详细程度的情况
使用仓库的标准上下文预算启发式方法，在脑海中估算提示词的token数量。
使用仓库的标准上下文预算启发式方法，在脑海中估算提示词的token数量。
对提示词进行分类，然后应用乘数范围获取完整响应窗口：
25% → min + (max - min) × 0.25 50% → min + (max - min) × 0.50 75% → min + (max - min) × 0.75 100% → max
SkillSignal prompt templates
These prompts were written by SkillSignal from the source structure; they are not upstream text.
Task-start prompt
Confirm source fit, inputs, and outputs before acting.
Use token-budget-advisor to help me with: [specific task]. Context: [files, data, or background]. Constraints: [environment, scope, and prohibited actions]. Before acting, check the pinned SKILL.md and explain which sections apply, what inputs are still missing, and what you will deliver.
Source-guided execution
Make the Agent explicitly follow the key extracted sections.
Apply the pinned token-budget-advisor source to [task]. Pay particular attention to these source sections: “何时使用”, “工作原理”, “第一步 — 估算输入token”, “第二步 — 按复杂度估算响应大小”, “第三步 — 呈现深度选项”. Preserve the important decision at each step. Mark facts not covered by the source as “needs confirmation” instead of inventing them. Then verify the result against my acceptance criteria: [criteria].
Result-review prompt
Check omissions, permissions, and source drift before delivery.
Review the current token-budget-advisor result: (1) does it satisfy the original task; (2) were any applicable steps or limits in the pinned SKILL.md missed; (3) did it perform any unauthorized file, command, network, or data action; and (4) which conclusions remain unverified? List issues first, then fix only what the source or user authorization supports.
Output checklist
The task matches the purpose documented in the SKILL.md.
The source section “何时使用” has been checked.
The source section “工作原理” has been checked.
The source section “第一步 — 估算输入token” has been checked.
The source section “第二步 — 按复杂度估算响应大小” has been checked.
Inputs, constraints, and acceptance criteria are explicit.
Unverified facts, compatibility, and outcome claims are clearly marked.
Any file, command, network, or data action has been reviewed.
Choose a different workflow
Offers the user an informed choice about how much response depth to consume before answering. Use this skill when the user explicitly wants to control response length, depth, or token budget. TRIGGER when: "token budget", "token count", "token usage", "token limit", "response length", "answer depth", "short version", "brief answer", "detailed answer", "exhaustive answer", "respuesta corta vs larga", "cuántos tokens", "ahorrar tokens", "responde al 50%", "dame la versión corta", "quiero controlar
A separate implementation from affaan-m/ECC; compare its source, maintenance signals, and permission requirements.
Open source detail回答する前に、どれだけの回答深度を消費するかについてユーザーに情報に基づいた選択を提供する。ユーザーが回答の長さ、深さ、またはトークンバジェットを明示的に制御したい場合にこのスキルを使用する。トリガー条件："token budget", "token count", "token usage", "token limit", "response length", "answer depth", "short version", "brief answer", "detailed answer", "exhaustive answer", "respuesta corta vs larga", "cuántos tokens", "ahorrar tokens", "responde al 50%", "dame la versión corta", "quiero controlar cuánto usas"、またはユーザーが回答のサイズや深さの制御を明示的に求めるその他の明確なバリエーション。トリガーしない条件：ユーザーが現在のセッションでレベルを指定済み（そのレベルを維持）、リクエ
A separate implementation from affaan-m/ECC; compare its source, maintenance signals, and permission requirements.
Open source detailWhen the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this," "which version is better," "test two versions," "statistical significance," "how long should I run this test," "growth experiments," "experiment velocity," "experiment backlog," "ICE score," "experimentation program
A separate implementation from coreyhaines31/marketingskills; compare its source, maintenance signals, and permission requirements.
Open source detailFAQ
在Claude回答之前拦截响应流程，让用户选择回答深度。
The catalog detected this source-specific install command: npx skills add https://github.com/affaan-m/ECC --skill "docs/zh-CN/skills/token-budget-advisor". Inspect the command and pinned source before running it.
No dedicated Agent platform is declared in the pinned source record.
Quality breakdown
Based on traceable docs and repository signals; stars are not treated as quality.
Compare before choosing
These links are selected from shared tasks, functions, stacks, platforms, and same-name variants. Compare the source owner, documentation, permissions, and maintenance signals.
Offers the user an informed choice about how much response depth to consume before answering. Use this skill when the user explicitly wants to control response length, depth, or token budget. TRIGGER when: "token budget", "token count", "token usage", "token limit", "response length", "answer depth", "short version", "brief answer", "detailed answer", "exhaustive answer", "respuesta corta vs larga", "cuántos tokens", "ahorrar tokens", "responde al 50%", "dame la versión corta", "quiero controlar
回答する前に、どれだけの回答深度を消費するかについてユーザーに情報に基づいた選択を提供する。ユーザーが回答の長さ、深さ、またはトークンバジェットを明示的に制御したい場合にこのスキルを使用する。トリガー条件："token budget", "token count", "token usage", "token limit", "response length", "answer depth", "short version", "brief answer", "detailed answer", "exhaustive answer", "respuesta corta vs larga", "cuántos tokens", "ahorrar tokens", "responde al 50%", "dame la versión corta", "quiero controlar cuánto usas"、またはユーザーが回答のサイズや深さの制御を明示的に求めるその他の明確なバリエーション。トリガーしない条件：ユーザーが現在のセッションでレベルを指定済み（そのレベルを維持）、リクエ
When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this," "which version is better," "test two versions," "statistical significance," "how long should I run this test," "growth experiments," "experiment velocity," "experiment backlog," "ICE score," "experimentation program
When the user wants to reduce churn, build cancellation flows, set up save offers, recover failed payments, or implement retention strategies. Also use when the user mentions 'churn,' 'cancel flow,' 'offboarding,' 'save offer,' 'dunning,' 'failed payment recovery,' 'win-back,' 'retention,' 'exit survey,' 'pause subscription,' 'involuntary churn,' 'people keep canceling,' 'churn rate is too high,' 'how do I keep users,' or 'customers are leaving.' Use this whenever someone is losing subscribers o
Grounded design brief from the adopted corpus — style, WCAG-checked color tokens, typography, layout pattern, anti-patterns. Use on ui-design-brief or any which-style/palette/font/chart decision.
在Claude回答之前拦截响应流程，让用户选择回答深度。
不要触发当：用户已在本会话中设置了级别（静默保持），或答案本身只有一行。
使用仓库的标准上下文预算启发式方法，在脑海中估算提示词的token数量。
使用与context-budget相同的校准指南：
words × 1.3chars / 4对于混合内容，使用主导内容类型并保持估算启发式方法。
对提示词进行分类，然后应用乘数范围获取完整响应窗口：
| 复杂度 | 乘数范围 | 示例提示词 |
|---|---|---|
| 简单 | 3× – 8× | "X是什么？"，是/否问题，单一事实 |
| 中等 | 8× – 20× | "X是如何工作的？" |
| 中高 | 10× – 25× | 带上下文的代码请求 |
| 复杂 | 15× – 40× | 多部分分析、比较、架构 |
| 创意 | 10× – 30× | 故事、散文、叙事写作 |
响应窗口 = input_tokens × mult_min 到 input_tokens × mult_max（但不要超过模型配置的输出token限制）。
在回答之前呈现此区块，使用实际估算的数字：
分析您的提示...
输入：~[N] 个令牌 | 类型：[类型] | 复杂度：[级别] | 语言：[语言]
选择您的深度级别：
[1] 基础 (25%) -> ~[令牌数] 直接回答，无开场白
[2] 适中 (50%) -> ~[令牌数] 回答 + 背景 + 1个示例
[3] 详细 (75%) -> ~[令牌数] 完整回答及备选方案
[4] 详尽 (100%) -> ~[令牌数] 全部内容，无限制
选择哪个级别？(1-4 或说 "25% 深度", "50% 深度", "75% 深度", "100% 深度")
精确度：启发式估计约 85-90% 准确率（±15%）。
各级别token估算（在响应窗口内）：
min + (max - min) × 0.25min + (max - min) × 0.50min + (max - min) × 0.75max| 级别 | 目标长度 | 包含内容 | 省略内容 |
|---|---|---|---|
| 25% 核心 | 最多2-4句话 | 直接回答、关键结论 | 上下文、示例、细微差别、替代方案 |
| 50% 适中 | 1-3个段落 | 答案+必要上下文+1个示例 | 深度分析、边界情况、参考文献 |
| 75% 详细 | 结构化回答 | 多个示例、优缺点、替代方案 | 极端边界情况、详尽参考文献 |
| 100% 详尽 | 无限制 | 一切内容——完整分析、所有代码、所有视角 | 无 |
如果用户已表明级别，立即按该级别回答，无需询问：
| 用户所说 | 级别 |
|---|---|
| "1" / "25%深度" / "简短版" / "简要回答" / "太长不看" | 25% |
| "2" / "50%深度" / "适中深度" / "平衡回答" | 50% |
| "3" / "75%深度" / "详细回答" / "全面回答" | 75% |
| "4" / "100%深度" / "详尽回答" / "完整深入分析" | 100% |
如果用户在本会话中已设置级别，后续回答静默保持该级别，除非用户更改。
此技能使用启发式估算——非真实分词器。准确率约85-90%，偏差±15%。始终显示免责声明。
来自TBA — Claude Code的Token预算顾问的独立技能。 原始项目还附带了一个Python估算脚本，但本仓库保持技能自包含且仅使用启发式方法。