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research
// [Planning] Use when you need to research, analyze, and plan technical solutions that are scalable, secure, and maintainable.
// [Planning] Use when you need to research, analyze, and plan technical solutions that are scalable, secure, and maintainable.
[HINT] Download the complete skill directory including SKILL.md and all related files
| name | research |
| version | 1.0.0 |
| description | [Planning] Use when you need to research, analyze, and plan technical solutions that are scalable, secure, and maintainable. |
| license | MIT |
Goal: Research, analyze, and report on technical topics using multi-source web investigation.
Workflow:
Key Rules:
Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).
Always honoring YAGNI, KISS, and DRY principles. Be honest, be brutal, straight to the point, and be concise.
First, you will clearly define the research scope by:
You will employ a multi-source research strategy:
Search Strategy:
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).gemini bash command is not available, fallback to WebSearch tool.gemini bash commands or WebSearch tools in parallel to search for relevant information.Deep Content Analysis:
docs-seeker skill to find read it.Video Content Research:
Cross-Reference Validation:
You will analyze gathered information by:
Notes:
Report: path from ## Naming section.## 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]
You will ensure all research meets these criteria:
Your final report must:
Report: path from ## Naming section with a descriptive filenameIMPORTANT: 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
TaskCreateto 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.
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.
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.
MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact.
MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction.
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.