Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · AI
context-engineer
Context window optimizer — analyze, audit, and optimize your agent's context utilization. Know exactly where your tokens go before they're sent.
skill openclawclawhub Free
Context window optimizer — analyze, audit, and optimize your agent's context utilization. Know exactly where your tokens go before they're sent.
⬇ 0 downloads ★ 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
- CHANGELOG.md, README.md, SKILL.md, context.py
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
- 1.0.2
Provenance
- Publisher
- tkuehnl
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
When to use this skill
Use this skill when the user wants to: Understand where their context window tokens are going Analyze workspace files (SKILL.md, SOUL.md, MEMORY.md, etc.) for bloat Audit tool definitions for redundancy and overhead Get a comprehensive context efficiency report Compare before/after snapshots to measure optimization progress Optimize system prompts for token efficiency
Commands
# Analyze workspace context files — token counts, efficiency scores, recommendations python3 skills/context-engineer/context.py analyze --workspace ~/.openclaw/workspace # Analyze with a custom budget and save a snapshot for later comparison python3 skills/context-engineer/context.py analyze --workspace ~/.openclaw/workspace --budget 128000 --snapshot before.json # Audit tool definitions for overhead and overlap python3 skills/context-engineer/context.py audit-tools --config ~/.openclaw/openclaw.json # Generate a comprehensive context engineering report python3 skills/context-engineer/context.py report --workspace ~/.openclaw/workspace --format terminal # Compare two snapshots to see projected token savings python3 skills/context-engineer/context.py compare --before before.json --after after.json
What It Analyzes
System prompt efficiency — Length, redundancy detection, compression potential Tool definition overhead — Count tools, per-tool token cost, identify unused/overlapping Memory file bloat — MEMORY.md size, stale entries, optimization suggestions Skill overhead — Installed skills contributing to context, per-skill token cost Context budget — What % of model context window is consumed by static content vs available for conversation
Options
--workspace PATH — Path to workspace directory (default: ~/.openclaw/workspace) --config PATH — Path to OpenClaw config file (default: ~/.openclaw/openclaw.json) --budget N — Context window token budget (default: 200000) --snapshot FILE — Save analysis snapshot to FILE for later comparison --format terminal — Output format (currently: terminal)
Notes
Token estimates are approximate (~4 characters per token). For precise counts, use a model-specific tokenizer. No external dependencies required — runs with Python 3 stdlib only. Built by Anvil AI — context engineering experts. https://anvil-ai.io
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
3 Docs1 Scripts
- SKILL.md
- CHANGELOG.md
- README.md
- context.py