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Merge pull request #920 from Xabilimon1/main
Add skill: token-budget-advisor (TBA)
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@@ -1,6 +1,6 @@
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# Everything Claude Code (ECC) — Agent Instructions
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This is a **production-ready AI coding plugin** providing 29 specialized agents, 132 skills, 60 commands, and automated hook workflows for software development.
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This is a **production-ready AI coding plugin** providing 30 specialized agents, 135 skills, 60 commands, and automated hook workflows for software development.
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**Version:** 1.9.0
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@@ -141,8 +141,8 @@ Troubleshoot failures: check test isolation → verify mocks → fix implementat
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## Project Structure
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```
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agents/ — 29 specialized subagents
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skills/ — 132 workflow skills and domain knowledge
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agents/ — 30 specialized subagents
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skills/ — 135 workflow skills and domain knowledge
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commands/ — 60 slash commands
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hooks/ — Trigger-based automations
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rules/ — Always-follow guidelines (common + per-language)
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@@ -220,7 +220,7 @@ For manual install instructions see the README in the `rules/` folder. When copy
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/plugin list everything-claude-code@everything-claude-code
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```
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✨ **That's it!** You now have access to 29 agents, 132 skills, and 60 commands.
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✨ **That's it!** You now have access to 30 agents, 135 skills, and 60 commands.
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### Multi-model commands require additional setup
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@@ -1109,9 +1109,9 @@ The configuration is automatically detected from `.opencode/opencode.json`.
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| Feature | Claude Code | OpenCode | Status |
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|---------|-------------|----------|--------|
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| Agents | ✅ 29 agents | ✅ 12 agents | **Claude Code leads** |
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| Agents | ✅ 30 agents | ✅ 12 agents | **Claude Code leads** |
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| Commands | ✅ 60 commands | ✅ 31 commands | **Claude Code leads** |
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| Skills | ✅ 132 skills | ✅ 37 skills | **Claude Code leads** |
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| Skills | ✅ 135 skills | ✅ 37 skills | **Claude Code leads** |
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| Hooks | ✅ 8 event types | ✅ 11 events | **OpenCode has more!** |
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| Rules | ✅ 29 rules | ✅ 13 instructions | **Claude Code leads** |
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| MCP Servers | ✅ 14 servers | ✅ Full | **Full parity** |
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@@ -408,6 +408,7 @@
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"skills/ralphinho-rfc-pipeline",
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"skills/regex-vs-llm-structured-text",
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"skills/search-first",
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"skills/token-budget-advisor",
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"skills/team-builder"
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],
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"targets": [
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131
skills/token-budget-advisor/SKILL.md
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131
skills/token-budget-advisor/SKILL.md
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---
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name: token-budget-advisor
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description: >-
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Intercepts the response flow to offer the user an informed choice about
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how much depth/tokens to consume — BEFORE responding. Use this skill
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when the user wants to control token consumption, adjust response depth,
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choose between short/long answers, or optimize their prompt.
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TRIGGER when: "token budget", "response token budget", "token count",
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"token usage", "response length", "response depth", "brief answer",
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"short answer", "detailed answer", "full answer",
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"respuesta corta vs larga", "cuántos tokens", "ahorrar tokens",
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"responde al 50%", "dame la versión corta", "quiero controlar cuánto usas",
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"75%", "100%", "at 25%", "at 50%", "at 75%", "at 100%",
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"give me the full answer", or any variant where the user wants
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to control length, depth, or token usage — even without mentioning tokens.
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DO NOT TRIGGER when: user has already specified a level in the current
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session (maintain it) or the request is clearly a one-word answer.
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origin: community
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---
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# Token Budget Advisor (TBA)
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Intercept the response flow to offer the user a choice about response depth **before** Claude answers.
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## When to Use
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- User wants to control how long or detailed a response is
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- User mentions tokens, budget, depth, or response length
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- User says "short version", "tldr", "brief", "al 25%", "exhaustive", etc.
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- Any time the user wants to choose depth/detail level upfront
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**Do not trigger** when: user already set a level this session (maintain it silently), or the answer is trivially one line.
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## How It Works
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### Step 1 — Estimate input tokens
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Use the repository's canonical estimation guidance from `skills/context-budget`.
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- Prose-first prompts: `input_tokens ≈ word_count × 1.3`
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- Code-heavy or mixed prompts: `input_tokens ≈ char_count / 4`
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For mixed content, prefer the code-heavy estimate as the conservative default.
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### Step 2 — Estimate response size by complexity
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Classify the prompt, then apply the multiplier range to get the full response window:
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| Complexity | Multiplier range | Example prompts |
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|--------------|------------------|------------------------------------------------------|
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| Simple | 3× – 8× | "What is X?", yes/no, single fact |
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| Medium | 8× – 20× | "How does X work?" |
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| Medium-High | 10× – 25× | Code request with context |
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| Complex | 15× – 40× | Multi-part analysis, comparisons, architecture |
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| Creative | 10× – 30× | Stories, essays, narrative writing |
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Response window = `input_tokens × mult_min` to `input_tokens × mult_max` (but don’t exceed your model’s configured output-token limit).
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### Step 3 — Present depth options
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Present this block **before** answering, using the actual estimated numbers:
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```
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Analyzing your prompt...
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Input: ~[N] tokens | Type: [type] | Complexity: [level] | Language: [lang]
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Choose your depth level:
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[1] Essential (25%) -> ~[tokens] Direct answer only, no preamble
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[2] Moderate (50%) -> ~[tokens] Answer + context + 1 example
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[3] Detailed (75%) -> ~[tokens] Full answer with alternatives
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[4] Exhaustive (100%) -> ~[tokens] Everything, no limits
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Which level? (1-4 or say "25%", "50%", "75%", "100%")
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Precision: heuristic estimate ~85-90% accuracy (±15%).
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```
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Level token estimates (within the response window):
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- 25% → `min + (max - min) × 0.25`
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- 50% → `min + (max - min) × 0.50`
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- 75% → `min + (max - min) × 0.75`
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- 100% → `max`
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### Step 4 — Respond at the chosen level
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| Level | Target length | Include | Omit |
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|------------------|---------------------|-----------------------------------------------------|---------------------------------------------------|
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| 25% Essential | 2-4 sentences max | Direct answer, key conclusion | Context, examples, nuance, alternatives |
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| 50% Moderate | 1-3 paragraphs | Answer + necessary context + 1 example | Deep analysis, edge cases, references |
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| 75% Detailed | Structured response | Multiple examples, pros/cons, alternatives | Extreme edge cases, exhaustive references |
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| 100% Exhaustive | No restriction | Everything — full analysis, all code, all perspectives | Nothing |
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## Shortcuts — skip the question
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If the user already signals a level, respond at that level immediately without asking:
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| What they say | Level |
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|----------------------------------------------------|-------|
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| "1" / "25%" / "short answer" / "brief" / "tldr" / "one-liner" | 25% |
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| "2" / "50%" / "moderate detail" / "balanced answer" | 50% |
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| "3" / "75%" / "detailed answer" / "thorough explanation" | 75% |
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| "4" / "100%" / "exhaustive" / "everything" / "full answer" | 100% |
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If the user set a level earlier in the session, **maintain it silently** for subsequent responses unless they change it.
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## Precision note
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This skill uses heuristic estimation — no real tokenizer. Accuracy ~85-90%, variance ±15%. Always show the disclaimer.
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## Examples
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### Triggers
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- "Give me the brief answer first."
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- "How many tokens will your response use?"
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- "Respond at 50% depth."
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- "I want the full answer."
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- "Dame la version corta."
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### Does Not Trigger
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- "Explain OAuth token refresh flow." (`token` here is domain language, not a budget request)
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- "Why is this JWT token invalid?" (security/domain usage, not response sizing)
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- "What is 2 + 2?" (trivially short answer)
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## Source
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Standalone skill from [TBA — Token Budget Advisor for Claude Code](https://github.com/Xabilimon1/Token-Budget-Advisor-Claude-Code-).
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The upstream project includes an optional estimator script, but this ECC skill intentionally stays zero-dependency and heuristic-only.
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