DNYoussef /============================================================================/ /* SKILL SKILL :: VERILINGUA x VERIX EDITION / /============================================================================*/
name: SKILL version: 1.0.0 description: | [assert|neutral] Analyze entire codebases with Gemini's 1 million token context window - process 30K lines at once [ground:given] [conf:0.95] [state:confirmed] category: platforms tags:
- gemini
- codebase-analysis
- architecture
- large-context
- multi-file author: system cognitive_frame: primary: compositional goal_analysis: first_order: "Execute SKILL workflow" second_order: "Ensure quality and consistency" third_order: "Enable systematic platforms processes"
/----------------------------------------------------------------------------/ /* S0 META-IDENTITY / /----------------------------------------------------------------------------*/
[define|neutral] SKILL := { name: "SKILL", category: "platforms", version: "1.0.0", layer: L1 } [ground:given] [conf:1.0] [state:confirmed]
/----------------------------------------------------------------------------/ /* S1 COGNITIVE FRAME / /----------------------------------------------------------------------------*/
[define|neutral] COGNITIVE_FRAME := { frame: "Compositional", source: "German", force: "Build from primitives?" } [ground:cognitive-science] [conf:0.92] [state:confirmed]
Kanitsal Cerceve (Evidential Frame Activation)
Kaynak dogrulama modu etkin.
/----------------------------------------------------------------------------/ /* S2 TRIGGER CONDITIONS / /----------------------------------------------------------------------------*/
[define|neutral] TRIGGER_POSITIVE := { keywords: ["SKILL", "platforms", "workflow"], context: "user needs SKILL capability" } [ground:given] [conf:1.0] [state:confirmed]
/----------------------------------------------------------------------------/ /* S3 CORE CONTENT / /----------------------------------------------------------------------------*/
Gemini Mega-Context Skill
Kanitsal Cerceve (Evidential Frame Activation)
Kaynak dogrulama modu etkin.
Purpose
Leverage Gemini CLI's massive 1 million token context window to analyze entire codebases, architectural patterns, and multi-file dependencies in a single pass - something Claude Code's context window cannot achieve.
Unique Capability
What Claude Code Can't Do: Claude Code has limited context window. Gemini 2.5 Pro can process up to 1 million tokens (~1,500 pages or 30,000 lines of code) simultaneously, enabling whole-codebase analysis without losing context.
When to Use
Perfect For:
✅ Analyzing entire project architecture ✅ Understanding multi-file dependencies across large codebases ✅ Refactoring that requires understanding the whole system ✅ Generating comprehensive documentation from full codebase ✅ Finding patterns and anti-patterns across all files ✅ Onboarding to unfamiliar large projects ✅ Security audits requiring full codebase awareness ✅ Migration planning (understand everything before changing)
Don't Use When:
❌ Working with single file or small module (use Claude Code) ❌ Need complex problem-solving (Claude is better) ❌ Writing new features (Gemini gets stuck in loops per user feedback) ❌ Need iterative refinement (Gemini switches to Flash after 5 min)
How It Works
This skill spawns a Gemini Mega-Context Agent that:
- Uses
gemini --all-filesto load your entire codebase - Leverages 1M token context for comprehensive analysis
- Returns architectural insights, dependency maps, or refactoring plans
- Provides results back to Claude Code for user presentation
Usage
Basic Codebase Analysis
/gemini-megacontext
With Specific Question
/gemini-megacontext "Explain the complete architecture and how all components interact"
Detailed Analysis
/gemini-megacontext "Map all database queries across the entire codebase and identify N+1 patterns"
Input Examples
# Architecture analysis
/gemini-megacontext "Document the full system architecture with component interactions"
# Dependency mapping
/gemini-megacontext "Create a dependency graph showing how all modules relate"
# Security audit
/gemini-megacontext "Identify all authentication and authorization patterns across the codebase"
# Migration planning
/gemini-megacontext "Analyze entire codebase for Python 2 to 3 migration requirements"
# Code patterns
/gemini-megacontext "Find all API endpoints and document their authentication methods"
# Refactoring scope
/gemini-megacontext "Identify all files that would need changes to rename User to Account"
Output
The agent provides:
- Architectural Overview: How the system is structured
- Component Interactions: How pieces fit together
- Dependency Map: What depends on what
- Pattern Analysis: Common patterns and anti-patterns found
- File References: Specific locations with file:line citations
- Recommendations: Improvement suggestions based on full context
Real-World Examples
Example 1: Architecture Documentation
Task: "Document our microservices architecture"
Agent analyzes all services simultaneously and provides:
- Service dependency graph
- API contract documentation
- Database schema relationships
- Authentication flow across services
- Configuration management patterns
Example 2: Refactoring Impact Analysis
Task: "If we change the User model, what breaks?"
Agent scans entire codebase and identifies:
- 47 files with direct User references
- 12 database migrations to update
- 8 API endpoints that return User data
- 15 frontend components displaying user info
- 3 background jobs processing users
Example 3: Security Audit
Task: "Find all places where we handle sensitive data"
Agent reviews full codebase and reports:
- All database fields storing PII
- API endpoints exposing sensitive data
- Logging statements that might leak secrets
- File upload ha
/*----------------------------------------------------------------------------*/
/* S4 SUCCESS CRITERIA */
/*----------------------------------------------------------------------------*/
[define|neutral] SUCCESS_CRITERIA := {
primary: "Skill execution completes successfully",
quality: "Output meets quality thresholds",
verification: "Results validated against requirements"
} [ground:given] [conf:1.0] [state:confirmed]
/*----------------------------------------------------------------------------*/
/* S5 MCP INTEGRATION */
/*----------------------------------------------------------------------------*/
[define|neutral] MCP_INTEGRATION := {
memory_mcp: "Store execution results and patterns",
tools: ["mcp__memory-mcp__memory_store", "mcp__memory-mcp__vector_search"]
} [ground:witnessed:mcp-config] [conf:0.95] [state:confirmed]
/*----------------------------------------------------------------------------*/
/* S6 MEMORY NAMESPACE */
/*----------------------------------------------------------------------------*/
[define|neutral] MEMORY_NAMESPACE := {
pattern: "skills/platforms/SKILL/{project}/{timestamp}",
store: ["executions", "decisions", "patterns"],
retrieve: ["similar_tasks", "proven_patterns"]
} [ground:system-policy] [conf:1.0] [state:confirmed]
[define|neutral] MEMORY_TAGGING := {
WHO: "SKILL-{session_id}",
WHEN: "ISO8601_timestamp",
PROJECT: "{project_name}",
WHY: "skill-execution"
} [ground:system-policy] [conf:1.0] [state:confirmed]
/*----------------------------------------------------------------------------*/
/* S7 SKILL COMPLETION VERIFICATION */
/*----------------------------------------------------------------------------*/
[direct|emphatic] COMPLETION_CHECKLIST := {
agent_spawning: "Spawn agents via Task()",
registry_validation: "Use registry agents only",
todowrite_called: "Track progress with TodoWrite",
work_delegation: "Delegate to specialized agents"
} [ground:system-policy] [conf:1.0] [state:confirmed]
/*----------------------------------------------------------------------------*/
/* S8 ABSOLUTE RULES */
/*----------------------------------------------------------------------------*/
[direct|emphatic] RULE_NO_UNICODE := forall(output): NOT(unicode_outside_ascii) [ground:windows-compatibility] [conf:1.0] [state:confirmed]
[direct|emphatic] RULE_EVIDENCE := forall(claim): has(ground) AND has(confidence) [ground:verix-spec] [conf:1.0] [state:confirmed]
[direct|emphatic] RULE_REGISTRY := forall(agent): agent IN AGENT_REGISTRY [ground:system-policy] [conf:1.0] [state:confirmed]
/*----------------------------------------------------------------------------*/
/* PROMISE */
/*----------------------------------------------------------------------------*/
[commit|confident] <promise>SKILL_VERILINGUA_VERIX_COMPLIANT</promise> [ground:self-validation] [conf:0.99] [state:confirmed]