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berlysia
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update-auto-approve

Analyze PermissionRequest decision logs to update auto-approve configurations across all layers.

9|Updated Aug 20, 2018
Search Tags:#testing#permissions#claude-code#logs-analysis#settings-json#auto-approval
One-click install
npx skills add https://github.com/berlysia/dotfiles --skill update-auto-approve
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: update-auto-approve
Source: https://github.com/berlysia/dotfiles/tree/main/.skills/update-auto-approve
Command: npx skills add https://github.com/berlysia/dotfiles --skill update-auto-approve

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Analyze PermissionRequest decision logs to identify unnecessary asks and propagate improvements to auto-approve configurations across all layers (settings.json patterns, static rule engine, LLM evaluator prompts, and tests), reducing manual review workload.

Core Features & Use Cases

  • End-to-end workflow across phases 1-5 to analyze logs, propose Layer 0/1 allow-list updates, expand SAFE_BASH_PATTERNS, and adjust LLM prompts.
  • Cross-layer optimization covering settings.json, static rules, and LLM evaluation to minimize false positives and bottlenecks.
  • Test-driven refinement with updated unit tests and safety checks to ensure uncertain decisions remain constrained.

Quick Start

Analyze Claude decision logs and update auto-approve rules across all layers.

Frequently Asked Questions about update-auto-approve

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I reduce unnecessary permission requests in Claude Code?▼

Analyze PermissionRequest decision logs to identify unnecessary asks, then propagate improvements to auto-approve configurations across settings.json patterns, static rule engines, and LLM evaluator prompts to minimize manual review workload.

What is the best way to update auto-approve rules based on logs analysis?▼

Run an end-to-end workflow across five phases: log analysis, Layer 0/1 allow-list updates, SAFE_BASH_PATTERNS expansion, LLM prompt adjustments, and test-driven deployment via chezmoi to comprehensively refine auto-approve rules.

Can I refine MCP tool allowances and Skill permissions using decision logs?▼

Yes, you can refine MCP tool allowances and Skill permissions by analyzing decision logs to expand SAFE_BASH_PATTERNS and adjust project-path patterns, applying cross-layer optimizations across settings.json, static rules, and LLM evaluation to minimize false positives and bottlenecks.

Does updating auto-approve configurations include safety checks for uncertain decisions?▼

Yes, updating auto-approve configurations includes test-driven refinement with updated unit tests and safety checks to ensure uncertain decisions remain constrained and do not get automatically approved.

How does cross-layer optimization work for Claude Code settings.json and LLM evaluator prompts?▼

Cross-layer optimization analyzes decision logs to simultaneously update settings.json patterns, static rule engines, and LLM evaluator prompts, reducing false positives and bottlenecks across all layers of the auto-approval workflow.

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