Pre-action boundary checking — validates agent tool calls against declared capabilities and task contracts
日本語の概要は準備中です。原文の説明を表示しています。
PostToolUse hook that compresses Playwright MCP tool output using Haiku summarization — Layer 4 of the token defense stack
インストール方法を見るインストールする前に、エージェントに与えられる指示の中身を確認できます。
Reduces Playwright MCP tool output tokens by 94-96% using intelligent Haiku summarization while preserving ref= values for interactive flow continuity.
MCP tool response (37K+ chars)
↓ PostToolUse hook
↓ playwright-compress.sh
↓ claude -p --model haiku (summarize)
↓ updatedMCPToolOutput (1.4K-1.9K chars)
| Layer | Component | Mechanism | Scope |
|---|---|---|---|
| 1 | cc-token-saver | Time-based budget alerts | Session |
| 2 | R013 Ecomode | Context-aware output compression | Agent |
| 3 | MAX_MCP_OUTPUT_TOKENS | Hard truncation (lossy) | Setting |
| 4 | playwright-compress | Intelligent summarization (lossless ref=) | Hook |
mcp__playwright__.* toolsref= attribute values are extracted and preserved in the summaryclaude -p), no API key needed| Rule | Interaction |
|---|---|
| R001 | No external data transmission — uses local claude -p |
| R013 | Complements Ecomode (Layer 2) with MCP-specific compression |
| R021 | Advisory PostToolUse hook — never blocks |
Configured in .claude/hooks/hooks.json PostToolUse section:
{
"matcher": "mcp_tool_name matches \"mcp__playwright__.*\" || mcp_tool_name matches \"mcp__claude-in-chrome__.*\"",
"hooks": [{
"type": "command",
"command": "bash .claude/hooks/scripts/playwright-compress.sh"
}],
"description": "Layer 4: Compress Playwright/Chrome MCP output via Haiku summarization"
}
Adapted from treesoop/claude-native-plugin playwright-optimizer (MIT).
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Pre-action boundary checking — validates agent tool calls against declared capabilities and task contracts
日本語の概要は準備中です。原文の説明を表示しています。
Auto-detect project context and optimize harness — deactivate unused agents/skills, suggest missing experts, generate project profile
日本語の概要は準備中です。原文の説明を表示しています。
Adversarial code review using attacker mindset — trust boundary, attack surface, business logic, and defense evaluation
日本語の概要は準備中です。原文の説明を表示しています。
Apache Airflow best practices for DAG authoring, testing, and production deployment
日本語の概要は準備中です。原文の説明を表示しています。
Alembic migration patterns for naming conventions, safety checks, expand-contract, env.py configuration, and CI integration
日本語の概要は準備中です。原文の説明を表示しています。
Pre-routing ambiguity analysis — scores request clarity and asks clarifying questions when needed (inspired by ouroboros)
日本語の概要は準備中です。原文の説明を表示しています。