token-budget-advisor

Original：🇺🇸 English

Translated

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.

1installs

Sourceaffaan-m/everything-claude-code

Added on2026-03-29

NPX Install

npx skill4agent add affaan-m/everything-claude-code token-budget-advisor

SKILL.md Content

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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.