By mocasus
🦴 paleo — personal token-saving skill collection (Claude Code / Codex / Gemini / Hermes). Compress output, trim context, cap token budget, condense conversation, summarize bulky output, compact JSON.
Use when you want automatic token-saving without manual skill selection. Auto-detects long sessions (>15 turns), high token usage, or bulky context — then auto-enables paleo + paleo-trim-context + paleo-converse + paleo-budget at safe defaults. User does not need to think about which skill is active. Off: "disable paleo-auto" / "manual paleo".
Use when user says "budget", "token limit", "stay under N tokens", or wants per-task token caps. Enforce a hard token budget per task/response — track estimate, stop before limit, summarize if exceeded. Off: "no budget" / "unlimited".
Use when user says "compress conversation", "condense chat", "summarize history", "too long context", or a session has many old turns. Condense prior conversation turns into a tight summary, merge near-duplicate messages, keep the last N turns verbatim. Saves context tokens without losing task state. Off: "stop condensing" / "keep full history".
Use when user says "compact json", "minify output", "tight structured", or the agent must emit JSON / structured data. Strip insignificant whitespace, collapse long arrays, shorten keys where safe, keep it parseable. Cuts tokens on structured payloads. Off: "pretty print" / "human-readable".
Use when user says "summarize output", "condense this", "tldr", or a tool result / log / file dump / long stdout is large. Reduce long content (tool output, logs, diffs, docs) to a concise intisari with key fields preserved. Saves context tokens on bulky payloads. Off: "full output" / "no summary".
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Token-saving skills for LLM agents — cut output & context tokens without choking the model.
Why · See it · Features · Skills · Combos · Quick Start · Benchmarks · Comparison · Tips · Install
SKILL.md is written terse on purpose — loading one costs less context than a long prompt.paleo compresses delivery, not meaning. Code, commands, and technical terms stay byte-exact.
| Normal agent | 🦴 paleo |
|---|---|
"The re-render happens because you create a new object literal on every render. That inline object is a fresh reference each time, so React sees a changed prop and re-renders. Wrap it in useMemo to keep a stable reference." | "New object each render → new ref → re-render. Wrap in useMemo. Stable ref = no re-render." |
| "To authenticate requests, add middleware that checks the token on each request and returns 401 if it is missing or expired." | "Add auth middleware. Check token per request. 401 if missing/expired." |
[!NOTE] paleo keeps technical accuracy at 100% — it drops filler, not facts.
paleo-auto watches session state and enables the right skills automatically. No thinking required.paleo-budget caps spend and summarizes the tail.npx skills add.SKILL.md is intentionally terse, so loading stays cheap.| Skill | What it does | Trigger example |
|---|---|---|
paleo | Terse output mode — cut output tokens ~50–70%, keep code/terms exact. | paleo mode · be brief · save tokens |
paleo-auto | 🆕 Zero-touch auto-detection — watches session & enables the right skills automatically. | paleo-auto · auto paleo · enable auto-save |
paleo-budget | Hard token budget per task — cap spend, summarize if exceeded. | budget 2000 · stay under 2000 tokens |
paleo-trim-context | Proactively trim/summarize context to save tokens without losing task state. | trim context (auto on long sessions) |
paleo-converse | Condense old chat turns + merge duplicate messages; keep last N verbatim. | condense chat · compress conversation · paleo-converse N=8 |
paleo-summary | Tight intisari of bulky tool output / logs / diffs / dumps. | tldr · condense this · summarize output |
paleo-json | Minify & compact structured/JSON output, stay parseable. | compact json · minify |
paleo is the base — keep it on. Layer the rest by what you're doing:
npx claudepluginhub mocasus/paleo --plugin paleojuliusbrussee/caveman — caveman
Honey (I Shrunk the AI) — three reflexive levers that cut agent token cost: less code (YAGNI/stdlib-first), less prose, and denser agent-to-agent handoffs (ESON/compact-JSON). Plus on-demand satellites (review, eco, gain, compress) and a hive of read-only subagents that return compressed handoffs. Auto-intensity lite/full/ultra; correctness and safety-critical paths stay exact.
Brief prose. Short common words. Trust context. State what matters. Omit what reader can infer.
Analyze and reduce Claude Code token overhead
Open-source, local-first Claude Code plugin for token reduction, context compression, and cost optimization using hybrid RAG retrieval (BM25 + vector search), reranking, AST-aware chunking, and compact context packets.
Verdict-first communication mode. Cuts output tokens while keeping full technical accuracy.