Create forensically sound bit-for-bit disk images using dd and dcfldd while preserving evidence integrity through hash verification.
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。
Transforms conversations and discussions into structured documentation pages in Notion. Captures insights, decisions, and knowledge from chat context, formats appropriately, and saves to wikis or databases with proper organization and linking for easy discovery.
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。
Transforms conversations, discussions, and insights into structured documentation in your Notion workspace. Captures knowledge from chat context, formats it appropriately, and saves it to the right location with proper organization and linking.
When asked to save information to Notion:
Notion:notion-search to find appropriate wiki page/databaseNotion:notion-create-pages to save contentFrom conversation context, extract:
- Key concepts and definitions
- Decisions made and rationale
- How-to information and procedures
- Important insights or learnings
- Q&A pairs
- Examples and use cases
Classify the knowledge:
- Concept/Definition
- How-to Guide
- Decision Record
- FAQ Entry
- Meeting Summary
- Learning/Post-mortem
- Reference Documentation
Format appropriately based on content type:
- Use templates for consistency
- Add clear headings and sections
- Include examples where helpful
- Add relevant metadata
- Link to related pages
Where to save:
- Wiki page (general knowledge base)
- Specific project page (project-specific knowledge)
- Documentation database (structured docs)
- FAQ database (questions and answers)
- Decision log (architecture/product decisions)
- Team wiki (team-specific knowledge)
Use Notion:notion-create-pages:
- Set appropriate title
- Use structured content from template
- Set properties if in database
- Add tags/categories
- Link to related pages
Link the new page so others can find it:
1. Update hub/index pages:
- Add link to wiki table of contents page
- Add link from relevant project page
- Add link from category/topic page (e.g., "Engineering Docs")
2. If page is in a database:
- Set appropriate tags/categories
- Set status (e.g., "Published")
- Add to relevant views
3. Optionally update parent page:
- If saved under a project, add to project's "Documentation" section
- If in team wiki, ensure it's linked from team homepage
Example:
Notion:notion-update-page
page_id: "team-wiki-homepage-id"
command: "insert_content_after"
selection_with_ellipsis: "## How-To Guides..."
new_str: "- <mention-page url='...'>How to Deploy to Production</mention-page>"
This step ensures the knowledge doesn't become "orphaned" - it's properly connected to your workspace's navigation structure.
Choose appropriate structure based on content:
Concept: Overview → Definition → Characteristics → Examples → Use Cases → Related How-To: Overview → Prerequisites → Steps (numbered) → Verification → Troubleshooting → Related Decision: Context → Decision → Rationale → Options Considered → Consequences → Implementation FAQ: Short Answer → Detailed Explanation → Examples → When to Use → Related Questions Learning: What Happened → What Went Well → What Didn't → Root Causes → Learnings → Actions
General Wiki: Standalone page → add to index → tag → link from related pages
Project Wiki: Child of project page → link from project overview → tag with project name
Documentation Database: Use properties (Title, Type, Category, Tags, Last Updated, Owner)
Decision Log Database: Use properties (Decision, Date, Status, Domain, Deciders, Impact)
FAQ Database: Use properties (Question, Category, Tags, Last Reviewed, Useful Count)
See reference/database-best-practices.md for database selection guide and individual schema files.
Chat Discussion: Key points, conclusions, resources, action items, Q&A
Problem-Solving: Problem statement, approaches tried, solution, why it worked, future considerations
Knowledge Sharing: Concept explained, examples, best practices, common pitfalls, resources
Decision Discussion: Question, options, trade-offs, decision, rationale, next steps
Structure: Use # (title), ## (sections), ### (subsections) consistently
Writing: Start with overview, use bullets, keep paragraphs short, add examples
Linking: Link related pages, mention people, reference resources, create bidirectional links
Metadata: Include date, author, tags, status
Searchability: Clear titles, natural keywords, common search tags, image alt-text
Wiki Index: Organize by sections (Getting Started, How-To Guides, Reference, FAQs, Decisions) with page links
Category Pages: Create landing pages with overview, doc links, and recent updates
Tagging Strategy: Use consistent tags for technology/tools, topics, audience, and status
Create New: Content is substantive (>2 paragraphs), will be referenced multiple times, part of knowledge base, needs independent discovery
Update Existing: Adding to existing topic, correcting info, expanding concept, updating for changes
Versioning: Add update history section for significant changes (date, author, what changed, why)
Documentation databases: See reference/database-best-practices.md for database schema patterns.
"Not sure where to save": Default to general wiki, can move later "Content is fragmentary": Group related fragments into cohesive doc "Already exists": Search first, update existing if appropriate "Too informal": Clean up language while preserving insights
See examples/ for complete workflows:
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概要と使いどころ
Create forensically sound bit-for-bit disk images using dd and dcfldd while preserving evidence integrity through hash verification.
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。
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
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。
Detect dangerous ACL misconfigurations in Active Directory using ldap3 to identify GenericAll, WriteDACL, and WriteOwner abuse paths
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。
Perform static analysis of Android APK malware samples using apktool for decompilation, jadx for Java source recovery, and androguard for permission analysis, manifest inspection, and suspicious API call detection.
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。
Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect BOLA/IDOR attacks, rate limit bypass, credential scanning, and injection attempts. Uses pandas for statistical analysis of request patterns and anomaly detection. Use when investigating API abuse or building API-specific threat detection rules.
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。
Analyze advanced persistent threat (APT) group techniques using MITRE ATT&CK Navigator to create layered heatmaps of adversary TTPs for detection gap analysis and threat-informed defense.
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。