token-budget-advisor
Skill0 starsChanged 4 months agoMITView on GitHub
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.
13 other projects use a version of this, 8 of them edited.
Adopted by
Most recently taken up by
- Rojios/everything-claude-codeedited, first seen Nov 8, 2026
- pankaj-mahaur/Agent-Daemonedited, first seen Nov 6, 2026
- davidanthonyn/claude-skillsedited, first seen Oct 20, 2026
- airshell/ai-optimizeredited, first seen Oct 17, 2026
- gongyijie85/dsh-eccword for word, first seen Oct 13, 2026
- NISTALTALSON/essential-claude-skillsword for word, first seen Oct 11, 2026
Other versions13 projects use a version of this.
Word for word · 3
- gongyijie85/dsh-ecc★ 8100% same
- NISTALTALSON/essential-claude-skills★ 1100% same
- SkotAlexsander/skills★ 1100% same
Edited · 8
- Fmarzochi/EGC★ 6198% same
- airshell/ai-optimizer★ 237% same
- Rojios/everything-claude-code★ 199% same
- SamuelNDCE/claude-super-skill-library★ 199% same
- TironFox/everything-claude-code★ 199% same
- davidanthonyn/claude-skills★ 099% same
- gesh75/claude-skills★ 092% same
- pankaj-mahaur/Agent-Daemon★ 098% same
Wrote their own version · 2
- Exploration-labs/Nates-Substack-Skills★ 55same name
- thanvish21/hcc-bundle★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository270 other files it gives its agents.
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- The first 60 shown.
The file
We split this skill into the rules it gives an agent
6 rules. 6 are common, 0 are distinctive, and 0 are very specific to this project.
6
Common
Most of the 9 edited versions we read keep these.
0
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Common: line 31
Do not trigger: when: user already set a level this session (maintain it silently), or the answer is trivially one line.
- Common: line 37
Use the repository's canonical context-budget heuristics to estimate the prompt's token count mentally.
- Common: line 39
Use the same calibration guidance as context-budget:
- Common: line 98
If the user already signals a level, respond at that level immediately without asking:
- Common: line 107
If the user set a level earlier in the session, maintain it silently for subsequent responses unless they change it.
- Common: line 129
Follow-up questions after the user already chose a depth for the session
“Common” is measured: kept by at least 6 in 10 of the 9 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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.
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