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[Planning] Use when you need to research, analyze, and plan technical solutions that are scalable, secure, and maintainable.

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SKILL.md

Full skill instructions

Quick Summary

Goal: Research, analyze, and report on technical topics using multi-source web investigation.

Workflow:

  1. Scope Definition — Identify key terms, recency needs, evaluation criteria
  2. Information Gathering — Use gemini CLI or WebSearch (max 5 searches), cross-reference sources
  3. Analysis & Synthesis — Identify patterns, pros/​cons, security/​performance implications
  4. Report Generation — Save structured markdown report with findings and recommendations

Key Rules:

  • Maximum 5 research tool calls per session
  • Prefer gemini CLI if available, fallback to WebSearch
  • Always cite sources and verify across multiple independent sources

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

Research

Research Methodology

Always honoring YAGNI, KISS, and DRY principles. Be honest, be brutal, straight to the point, and be concise.

Phase 1: Scope Definition

First, you will clearly define the research scope by:

  • Identifying key terms and concepts to investigate
  • Determining the recency requirements (how current must information be)
  • Establishing evaluation criteria for sources
  • Setting boundaries for the research depth

Phase 2: Systematic Information Gathering

You will employ a multi-source research strategy:

  1. Search Strategy:

    • Check if gemini bash command is available, if so, execute gemini -m gemini-2.5-flash -p "...your search prompt..." bash command (timeout: 10 minutes) and save the output using Report: path from ## Naming section (including all citations).
    • If gemini bash command is not available, fallback to WebSearch tool.
    • Run multiple gemini bash commands or WebSearch tools in parallel to search for relevant information.
    • Craft precise search queries with relevant keywords
    • Include terms like "best practices", "2024", "latest", "security", "performance"
    • Search for official documentation, GitHub repositories, and authoritative blogs
    • Prioritize results from recognized authorities (official docs, major tech companies, respected developers)
    • IMPORTANT: You are allowed to perform at most 5 researches (max 5 tool calls), user might request less than this amount, strictly respect it, think carefully based on the task before performing each related research topic.

  2. Deep Content Analysis:

    • When you found a potential Github repository URL, use docs-seeker skill to find read it.
    • Focus on official documentation, API references, and technical specifications
    • Analyze README files from popular GitHub repositories
    • Review changelog and release notes for version-specific information

  3. Video Content Research:

    • Prioritize content from official channels, recognized experts, and major conferences
    • Focus on practical demonstrations and real-world implementations

  4. Cross-Reference Validation:

    • Verify information across multiple independent sources
    • Check publication dates to ensure currency
    • Identify consensus vs. controversial approaches
    • Note any conflicting information or debates in the community

Phase 3: Analysis and Synthesis

You will analyze gathered information by:

  • Identifying common patterns and best practices
  • Evaluating pros and cons of different approaches
  • Assessing maturity and stability of technologies
  • Recognizing security implications and performance considerations
  • Determining compatibility and integration requirements

Phase 4: Report Generation

Notes:

  • Research reports are saved using Report: path from ## Naming section.
  • If ## Naming section is not available, ask main agent to provide the output path.

You will create a comprehensive markdown report with the following structure:

# Research Report: [Topic]

## Executive Summary

[2-3 paragraph overview of key findings and recommendations]

## Research Methodology

- Sources consulted: [number]
- Date range of materials: [earliest to most recent]
- Key search terms used: [list]

## Key Findings

### 1. Technology Overview

[Comprehensive description of the technology/​topic]

### 2. Current State & Trends

[Latest developments, version information, adoption trends]

### 3. Best Practices

[Detailed list of recommended practices with explanations]

### 4. Security Considerations

[Security implications, vulnerabilities, and mitigation strategies]

### 5. Performance Insights

[Performance characteristics, optimization techniques, benchmarks]

## Comparative Analysis

[If applicable, comparison of different solutions/​approaches]

## Implementation Recommendations

### Quick Start Guide

[Step-by-step getting started instructions]

### Code Examples

[Relevant code snippets with explanations]

### Common Pitfalls

[Mistakes to avoid and their solutions]

## Resources & References

### Official Documentation

- [Linked list of official docs]

### Recommended Tutorials

- [Curated list with descriptions]

### Community Resources

- [Forums, Discord servers, Stack Overflow tags]

### Further Reading

- [Advanced topics and deep dives]

## Appendices

### A. Glossary

[Technical terms and definitions]

### B. Version Compatibility Matrix

[If applicable]

### C. Raw Research Notes

[Optional: detailed notes from research process]

Quality Standards

You will ensure all research meets these criteria:

  • Accuracy: Information is verified across multiple sources
  • Currency: Prioritize information from the last 12 months unless historical context is needed
  • Completeness: Cover all aspects requested by the user
  • Actionability: Provide practical, implementable recommendations
  • Clarity: Use clear language, define technical terms, provide examples
  • Attribution: Always cite sources and provide links for verification

Special Considerations

  • When researching security topics, always check for recent CVEs and security advisories
  • For performance-related research, look for benchmarks and real-world case studies
  • When investigating new technologies, assess community adoption and support levels
  • For API documentation, verify endpoint availability and authentication requirements
  • Always note deprecation warnings and migration paths for older technologies

Output Requirements

Your final report must:

  1. Be saved using the Report: path from ## Naming section with a descriptive filename
  2. Include a timestamp of when the research was conducted
  3. Provide clear section navigation with a table of contents for longer reports
  4. Use code blocks with appropriate syntax highlighting
  5. Include diagrams or architecture descriptions where helpful (in mermaid or ASCII art)
  6. Conclude with specific, actionable next steps

IMPORTANT: Sacrifice grammar for the sake of concision when writing reports. IMPORTANT: In reports, list any unresolved questions at the end, if any.

Remember: You are not just collecting information, but providing strategic technical intelligence that enables informed decision-making. Your research should anticipate follow-up questions and provide comprehensive coverage of the topic while remaining focused and practical.

[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.

<!-- SYNC:ai-mistake-prevention -->

AI Mistake Prevention — Failure modes to avoid on every task:

Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal. Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing. Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain. Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path. When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site. Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code. Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks. Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis. Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly. Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path. Keep domain concepts out of generic/​shared/​infrastructure layers. A reusable layer (shared library, framework, infra module) must reference NO consumer-specific domain concept — tenant/​customer/​product IDs, business entities, feature rules. The leak compiles and runs, so it passes review silently while coupling the "reusable" layer to one consumer. Push domain fields/​logic down into the consumer via subclass or composition.

<!-- /​SYNC:ai-mistake-prevention --> <!-- SYNC:critical-thinking-mindset -->

Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.

<!-- /​SYNC:critical-thinking-mindset --> <!-- SYNC:critical-thinking-mindset:reminder -->

MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact.

<!-- /​SYNC:critical-thinking-mindset:reminder --> <!-- SYNC:ai-mistake-prevention:reminder -->

MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction.

<!-- /​SYNC:ai-mistake-prevention:reminder -->

Closing Reminders

IMPORTANT MUST ATTENTION break work into small todo tasks using TaskCreate BEFORE starting IMPORTANT MUST ATTENTION search codebase for 3+ similar patterns before creating new code IMPORTANT MUST ATTENTION cite file:line evidence for every claim (confidence >80% to act) IMPORTANT MUST ATTENTION add a final review todo task to verify work quality

[TASK-PLANNING] Before acting, analyze task scope and systematically break it into small todo tasks and sub-tasks using TaskCreate.