Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Token Saver 75+
Automatically classifies requests to optimize cost by routing to the cheapest capable model and applies maximum output compression for 75%+ token savings.
skill openclawclawhub Free
Automatically classifies requests to optimize cost by routing to the cheapest capable model and applies maximum output compression for 75%+ token savings.
β¬ 0 downloads β
0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- README.md, SKILL.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- mariovallereyes
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Core Principle
Understand fully, execute cheaply. The orchestrator must fully understand the task before routing. Never sacrifice comprehension for speed.
Request Classifier (silent, every message)
TierPatternOrchestratorExecutorT1yes/no, status, trivial facts, quick lookupsHandle aloneβT2summaries, how-to, lists, bulk processing, formattingHandle alone OR spawn GroqGroq (FREE)T3debugging, multi-step, code generation, structured analysisOrchestrate + spawnCodex for code, Groq for bulkT4strategy, complex decisions, multi-agent coordination, creativeSpawn OpusOpus orchestrates, spawns Codex/Groq from within
Model Routing Table
ModelUse ForCostSpawn withgroq/llama-3.1-8b-instantSummarization, formatting, classification, bulk transforms β NO thinkingFREEmodel: "groq/llama-3.1-8b-instant"openai/gpt-5.3-codexALL code generation, code review, refactoring$$$model: "openai/gpt-5.3-codex"openai/gpt-5.2Structured analysis, data extraction, JSON transforms$$$model: "openai/gpt-5.2"anthropic/claude-opus-4-6Strategy, complex orchestration, failure recovery (T4 only)$$$$model: "anthropic/claude-opus-4-6"
When to spawn (MANDATORY)
Code generation of any kind β spawn Codex Bulk text processing (>3 items) β spawn Groq Complex multi-step tasks β spawn Opus (T4) Simple formatting/rewriting β spawn Groq
When NOT to spawn
T1 questions (yes/no, time, status) β handle directly Single tool calls (calendar, web search) β handle directly Short responses that need no processing β handle directly
Spawn patterns
Groq (free bulk work): sessions_spawn( task: "<clear instruction with all context included>", model: "groq/llama-3.1-8b-instant" ) Codex (all code): sessions_spawn( task: "Write <language> code that <detailed spec>. Include comments. Output the complete file.", model: "openai/gpt-5.3-codex" ) Opus (T4 strategy): sessions_spawn( task: "<full context + goal>. You have full tool access. Use sessions_spawn with Codex for code and Groq for bulk subtasks.", model: "anthropic/claude-opus-4-6" )
Critical spawn rules
Include ALL context in the task string β spawned agents have no conversation history Be specific β vague tasks waste tokens on clarification One task per spawn β don't bundle unrelated work For code: always use Codex β never write code yourself
Templates
STATUS: OK/WARN/FAIL one-liner CHOICE: A vs B β Recommend: X (1 line why) CAUSEβFIXβVERIFY: 3 bullets max RESULT: data/output directly, no wrap-up
Rules
No filler. No restating the question. Lead with the answer. Bullets/tables/code > prose. Do not narrate routine tool calls. If user asks for depth ("why", "explain", "go deep") β allow more tokens for that turn only.
Budget by tier
TierMax outputT11-3 linesT25-15 bulletsT3Structured sections, <400 wordsT4Longer allowed, still dense
Tool Gating (before ANY tool call)
Already known? β No tool. Batchable? β Parallelize. Can a spawned Groq handle it? β Spawn instead of doing it yourself. Cheapest path? β memory_search > partial read > full read > web. Needed? β Do not fetch "just in case."
Failure Protocol
If Groq spawn fails β retry with GPT-5.2 If Codex spawn fails β retry with GPT-5.2 If orchestrator can't handle T3 β spawn Opus (escalate to T4) Never retry same model. Escalate.
Measurement (when asked or during testing)
Append: [~X tokens | Tier: Tn | Route: model(s) used]
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
2 Docs
- SKILL.md
- README.md