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Visualize the current context window usage — token estimates per component (system prompt, tools, workspace files, messages, free space). Use when the user asks about context size, token usage, context breakdown, "how full is the context", or wants to see what's consuming their context window.
请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。
SkillHub CLI
skillhub install furukama/context-viz打开来源仓库,查看说明和兼容环境后,按来源提供的命令或步骤安装。
将来源链接提供给你的 Agent,让它先读取说明、核对依赖,并向你说明将执行的安装步骤。
Estimate and display a breakdown of the current context window usage.
Run the bundled script to estimate token counts for workspace files:
python3 scripts/estimate_tokens.py /path/to/workspace
The script counts characters in known workspace files and estimates tokens (~4 chars/token).
Then call session_status to get the actual context usage from OpenClaw.
session_status to get: model, context used/total, compactionsscripts/estimate_tokens.py <workspace_path> to estimate file token sizescontext_used - system_overhead - file_tokens
Use a monospace block with bar chart. Adapt the bar lengths proportionally.
📊 Context Usage
<model> • <used>k/<total>k tokens (<pct>%)
Component Tokens %
─────────────────────────────────────────────
⚙️ System prompt + tools ~Xk X% ░░
📋 AGENTS.md ~Xk X% ░
👻 SOUL.md ~Xk X%
👤 USER.md ~Xk X%
🔧 TOOLS.md ~Xk X% ░
💓 HEARTBEAT.md ~Xk X%
🧠 MEMORY.md ~Xk X% ░
🪪 IDENTITY.md ~Xk X%
💬 Messages ~Xk X% ░░░░░░░░░░░░
📭 Free space ~Xk X% ░░░░░
─────────────────────────────────────────────
Use ░ blocks: 1 block per ~2% of total context. Round to nearest block.
Below the context chart, add a Memory on Disk section showing what's stored in memory/ — grouped by category. These files are NOT loaded into context but represent the agent's total knowledge base.
💾 Memory on Disk (not in context)
Category Files Tokens Size
──────────────────────────────────────────────────
📰 chinese-ai-digests 12 ~23k...
这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。
# Context Visualization Estimate and display a breakdown of the current context window usage. ## How It Works Run the bundled script to estimate token counts for workspace files: ```bash python3 scripts/estimate_tokens.py /path/to/workspace ``` The script counts characters in known workspace files and estimates tokens (~4 chars/token). Then call `session_status` to get the actual context usage from OpenClaw. ## Generating the Visualization 1. Run `session_status` to get: model, context used/total, compactions 2. Run `scripts/estimate_tokens.py <workspace_path>` to estimate file token sizes 3. Estimate message tokens: `context_used - system_overhead - file_tokens` 4. Present the breakdown using the format below ## Output Format Use a monospace block with bar chart. Adapt the bar lengths proportionally. ``` 📊 Context Usage <model> • <used>k/<total>k tokens (<pct>%) Component Tokens % ───────────────────────────────────────────── ⚙️ System prompt + tools ~Xk X% ░░ 📋 AGENTS.md ~Xk X% ░ 👻 SOUL.md ~Xk X% 👤 USER.md ~Xk X% 🔧 TOOLS.md ~Xk X% ░ 💓 HEARTBEAT.md ~Xk X% 🧠 MEMORY.md ~Xk X% ░ 🪪 IDENTITY.md ~Xk X% 💬 Messages ~Xk X% ░░░░░░░░░░░░ 📭 Free space ~Xk X% ░░░░░ ───────────────────────────────────────────── ``` Use ░ blocks: 1 block per ~2% of total context. Round to nearest block. ## Memory Inventory (not in context) Below the context chart, add a **Memory on Disk** section showing what's stored in `memory/` — grouped by category. These files are NOT loaded into context but represent the agent's total knowledge base. ``` 💾 Memory on Disk (not in context) Category Files Tokens Size ────────────────────────────────────────────────── 📰 chinese-ai-digests 12 ~23k...
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