先看看示例
作者提供的示例，实际效果取决于你的输入和使用工具。
输入
用户要求先给短版再给详版，先输出25%要点，再按75%展开示例与对比。
输出
预期交付：深度选项与令牌估算、对应详略程度的回答（编辑说明，非实际运行结果）
方法说明
--- name: token-budget-advisor description: Offer a choice of response depth (25%/50%/75%/100%) with token estimates before answering, then answer at that level. Use when the user asks to control response length or token budget, such as 'token budget', 'short version', 'brief answer', 'respuesta corta vs larga', 'cuántos tokens', 'ahorrar tokens', 'responde al 50%', 'dame la versión corta', 'quiero controlar cuánto usas'. Skip if depth is already set this session or 'token' means an auth/payment token. metadata: origin: community --- # Token Budget Advisor (TBA) Intercept the response flow to offer the user a choice about response depth **before** Claude answers. ## When to Use - User wants to control how long or detailed a response is - User mentions tokens, budget, depth, or response length - User says "short version", "tldr", "brief", "al 25%", "exhaustive", etc. - Any time the user wants to choose depth/detail level upfront **Do not trigger** when: user already set a level this session (maintain it silently), or the answer is trivially one line. ## How It Works ### Step 1 — Estimate input tokens Use the repository's canonical context-budget heuristics to estimate the prompt's token count mentally. Use the same calibration guidance as [context-budget](../context-budget/SKILL.md): - prose: `words × 1.3` - code-heavy or mixed/code blocks: `chars / 4` For mixed content, use the dominant content type and keep the estimate heuristic. ### Step 2 — Estimate response size by complexity Classify the prompt, then apply the multiplier range to get the full response window: | Complexity | Multiplier range | Example prompts | |--------------|------------------|------------------------------------------------------| | Simple | 3× – 8× | "What is X?", yes/no, single fact | | Medium | 8× – 20× | "How does X work?" | | Medium-High | 10× – 25× | Code request with context | | Complex | 15× – 40× | Multi-part analysis, comparisons, architecture | | Creative | 10× – 30× | Stories, essays, narrative writing | Response window = `input_tokens × mult_min` to `input_tokens × mult_max` (but don’t exceed your model’s configured output-token limit). ### Step 3 — Present depth options Present this block **before** answering, using the actual estimated numbers: ``` Analyzing your prompt... Input: ~[N] tokens | Type: [type] | Complexity: [level] | Language: [lang] Choose your depth level: [1] Essential (25%) -> ~[tokens] Direct answer only, no preamble [2] Moderate (50%) -> ~[tokens] Answer + context + 1 example [3] Detailed (75%) -> ~[tokens] Full answer with alternatives [4] Exhaustive (100%) -> ~[tokens] Everything, no limits Which level? (1-4 or say "25% depth", "50% depth", "75% depth", "100% depth") Precision: heuristic estimate ~85-90% accuracy (±15%). ``` Level token estimates (within the response window): - 25% → `min + (max - min) × 0.25` - 50% → `min + (max - min) × 0.50` - 75% → `min + (max - min) × 0.75` - 100% → `max` ### Step 4 — Respond at the chosen level | Level | Target length | Include | Omit | |------------------|---------------------|-----------------------------------------------------|---------------------------------------------------| | 25% Essential | 2-4 sentences max | Direct answer, key conclusion | Context, examples, nuance, alternatives | | 50% Moderate | 1-3 paragraphs | Answer + necessary context + 1 example | Deep analysis, edge cases, references | | 75% Detailed | Structured response | Multiple examples, pros/cons, alternatives | Extreme edge cases, exhaustive references | | 100% Exhaustive | No restriction | Everything — full analysis, all code, all perspectives | Nothing | ## Shortcuts — skip the question If the user already signals a level, respond at that level immediately without asking: | What they say | Level | |----------------------------------------------------|-------| | "1" / "25% depth" / "short version" / "brief answer" / "tldr" | 25% | | "2" / "50% depth" / "moderate depth" / "balanced answer" | 50% | | "3" / "75% depth" / "detailed answer" / "thorough answer" | 75% | | "4" / "100% depth" / "exhaustive answer" / "full deep dive" | 100% | If the user set a level earlier in the session, **maintain it silently** for subsequent responses unless they change it. ## Precision note This skill uses heuristic estimation — no real tokenizer. Accuracy ~85-90%, variance ±15%. Always show the disclaimer. ## Examples ### Triggers - "Give me the short version first." - "How many tokens will your answer use?" - "Respond at 50% depth." - "I want the exhaustive answer, not the summary." - "Dame la version corta y luego la detallada." ### Does Not Trigger - "What is a JWT token?" - "The checkout flow uses a payment token." - "Is this normal?" - "Complete the refactor." - Follow-up questions after the user already chose a depth for the session ## Source Standalone skill from [TBA — Token Budget Advisor for Claude Code](https://github.com/Xabilimon1/Token-Budget-Advisor-Claude-Code-). Original project also ships a Python estimator script, but this repository keeps the skill self-contained and heuristic-only.