Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Developer Tools
Json Render Table
Render compact generic data tables to PNG images with json-render-cli. Use when users ask to visualize arbitrary structured rows/columns (non-ticket-specific...
skill openclawclawhub Free
Render compact generic data tables to PNG images with json-render-cli. Use when users ask to visualize arbitrary structured rows/columns (non-ticket-specific...
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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
- SKILL.md, agents/openai.yaml, references/compact-table-spec.template.json, references/compact-table-template.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
- 0.2.0
Provenance
- Publisher
- sorphwer
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Overview
Render generic structured data into compact table images using json-render-cli components (Column, Row, Container, Text, Badge). Use this skill for non-ticket table use cases.
Workflow
Ensure json-render is available. If missing, run npm i -g json-render-cli; if Chromium is missing, run npx playwright install chromium. Define target columns and row schema for the current dataset. Generate message JSON in memory from the table template. Pass config via process substitution (-c <(...)) to avoid temporary config files. Set screenshot.fullPage=true when row count or line wrapping is variable. Tune viewport width/height to the current content footprint before final render, and avoid oversized fixed --size. Render PNG and return output path (or Base64 only when explicitly requested). Theme mode is configured with theme.mode; use system by default, or force light / dark when needed.
Agent Coordination
Prefer rendering in the current (main) agent when the image must be delivered in the same turn. Delegate rendering to a sub-agent only when output-path handoff is explicit and deterministic. Keep rendered PNG files intact in sub-agent execution; do not delete or move them there. Perform garbage collection only in the main agent, and only after delivery succeeds.
Model Routing
If the current assistant model is high-cost (for example, Opus-class), route simple deterministic rendering to a lower-cost fast model (for example, gemini3flash) only when Agent Coordination rules can be enforced; otherwise render in the current main agent.
Use Case Selection
Generic table: use references/compact-table-template.md. Ticket-focused table: use json-render-ticket-table. Information cards (KPI/compare/summary): use json-render-info-cards. Announcement/hero cards: use json-render-announcement-cards. Flow/timeline summaries: use json-render-flow-summary.
Build And Render
Use references/compact-table-template.md. Treat the included template as an executable starter and customize columns and widths per dataset. Default style: No title area Compact header + body Edge-to-edge screenshot Stable column widths Bottom rows remain visible (screenshot.fullPage=true)
Layout Rules
Define columns with Row + Container and explicit widths. Keep spacing compact and deterministic. Use Badge only for categorical status-like fields. Resize the widest column first when content overflows. Keep viewport width close to the sum of column widths and avoid large horizontal slack. Start from a compact viewport height and expand only when clipping appears.
Output Rules
Prefer -o /tmp/<name>.png for image delivery. Use -o stdout only when caller explicitly asks for Base64. Avoid temporary JSON files unless explicitly requested. If a sub-agent renders the PNG, return path only and skip cleanup in that sub-agent. Run final PNG cleanup only in the main agent after image delivery.
Troubleshooting
If Chromium is missing, run: npx playwright install chromium. If rendering is too wide, reduce wide columns or font size. If left/right whitespace is too large, decrease viewport width or topic column width and rerender. If top/bottom whitespace is too large, decrease viewport height and rerender. If bottom rows are clipped, enable screenshot.fullPage=true.
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
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Package contents
Included in package
2 Docs2 Config
- SKILL.md
- references/compact-table-template.md
- agents/openai.yaml
- references/compact-table-spec.template.json