Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Advisory Committee
4-agent AI advisory committee for strategic decisions. Runs CS, Marketing, Finance, and Tech agents in sequence to analyze proposals and deliver a majority-v...
skill openclawclawhub Free
4-agent AI advisory committee for strategic decisions. Runs CS, Marketing, Finance, and Tech agents in sequence to analyze proposals and deliver a majority-v...
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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
- references/committee-roles.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. 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. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.1.0
Provenance
- Publisher
- jini92
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
How It Works
When given a proposal, run the following 4 agents in sequence. Each agent judges independently.
Agent Order
π§ CS Agent "User Champion" β User value perspective π£ Marketing Agent "Growth Hacker" β Distribution/growth perspective π¦ Finance Agent "CFO" β ROI/priority perspective π§ Tech Agent "CTO" β Implementation/complexity perspective Each agent verdict: β YES / β NO / β οΈ Conditional
Output Format
## ποΈ Committee β [Proposal] ### π§ CS β [β /β/β οΈ] > [2~3 lines of reasoning] ### π£ Marketing β [β /β/β οΈ] > [2~3 lines of reasoning] ### π¦ Finance β [β /β/β οΈ] > [2~3 lines of reasoning] ### π§ Tech β [β /β/β οΈ] > [2~3 lines of reasoning] ## π Recommendation **Decision: [YES / NO / Conditional]** > [One-line action]
Agent Criteria
For detailed judgment criteria per agent, see references/committee-roles.md.
Decision Log
After each decision, append a row to the decision log table: DateProposalCSMarketingFinanceTechDecision
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
- references/committee-roles.md