token-budget-advisor

name token-budget-advisor description 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 cuánto usas", or clear variants where the user is explicitly asking to control answer size or depth. DO NOT TRIGGER when: user has already specified a level in the current session (maintain it), the request is clearly a one-word answer, or "token" refers to auth/session/payment tokens rather than response size. 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 : 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 . Original project also ships a Python estimator script, but this repository keeps the skill self-contained and heuristic-only.