### 1. File Analysis Phase
**Read and Parse File**:
Read the target `.agent.md` or `.prompt.md` file
Extract frontmatter (description, mode, tools, model if specified)
Analyze body content to identify:
Task complexity (simple/moderate/complex/advanced)
Required reasoning depth (basic/intermediate/advanced/expert)
Code generation needs (minimal/moderate/extensive)
Multi-turn conversation requirements
Context window needs (small/medium/large)
Specialized capabilities (image analysis, long-context, real-time data)
**Categorize Task Type**:
Identify the primary task category based on content analysis:
1Simple Repetitive Tasks — :
Pattern: Formatting, simple refactoring, adding comments/docstrings, basic CRUD
Characteristics: Straightforward logic, minimal context, fast execution preferred
Keywords: format, comment, simple, basic, add docstring, rename, move
2Code Generation & Implementation — :
Pattern: Writing functions/classes, implementing features, API endpoints, tests
Characteristics: Moderate complexity, domain knowledge, idiomatic code
Keywords: implement, create, generate, write, build, scaffold
3Complex Refactoring & Architecture — :
Pattern: System design, architectural review, large-scale refactoring, performance optimization
Characteristics: Deep reasoning, multiple components, trade-off analysis
Keywords: architect, refactor, optimize, design, scale, review architecture
4Debugging & Problem-Solving — :
Pattern: Bug fixing, error analysis, systematic troubleshooting, root cause analysis
Characteristics: Step-by-step reasoning, debugging context, verification needs
Keywords: debug, fix, troubleshoot, diagnose, error, investigate
Pattern: Feature planning, research, documentation analysis, ADR creation
Characteristics: Read-only, context gathering, decision-making support
Keywords: plan, research, analyze, investigate, document, assess
6Code Review & Quality Analysis — :
Pattern: Security analysis, performance review, best practices validation, compliance checking
Characteristics: Critical thinking, pattern recognition, domain expertise
Keywords: review, analyze, security, performance, compliance, validate
7Specialized Domain Tasks — :
Pattern: Django/framework-specific, accessibility (WCAG), testing (TDD), API design
Characteristics: Deep domain knowledge, framework conventions, standards compliance
Keywords: django, accessibility, wcag, rest, api, testing, tdd
8Advanced Reasoning & Multi-Step Workflows — :
Pattern: Algorithmic optimization, complex data transformations, multi-phase workflows
Characteristics: Advanced reasoning, mathematical/algorithmic thinking, sequential logic
Keywords: algorithm, optimize, transform, sequential, reasoning, calculate
**Extract Capability Requirements**:
Based on `tools` in frontmatter and body instructions:
**Read-only tools** (search, fetch, usages, githubRepo): Lower complexity, faster models suitable
**Write operations** (edit/editFiles, new): Moderate complexity, accuracy important
**Execution tools** (runCommands, runTests, runTasks): Validation needs, iterative approach
**Advanced tools** (context7/\*, sequential-thinking/\*): Complex reasoning, premium models beneficial
**Multi-modal** (image analysis references): Requires vision-capable models
### 2. Model Evaluation Phase
**Apply Model Selection Criteria**:
For each available model, evaluate against these dimensions:
#### Model Capabilities Matrix
| Model | Multiplier | Speed | Code Quality | Reasoning | Context | Vision | Best For |
| ----------------------- | ---------- | -------- | ------------ | --------- | ------- | ------ | ------------------------------------------------- |
| GPT-4.1 | 0x | Fast | Good | Good | 128K | ✅ | Balanced general tasks, included in all plans |
| GPT-5 mini | 0x | Fastest | Good | Basic | 128K | ❌ | Simple tasks, quick responses, cost-effective |
| GPT-5 | 1x | Moderate | Excellent | Advanced | 128K | ✅ | Complex code, advanced reasoning, multi-turn chat |
| GPT-5 Codex | 1x | Fast | Excellent | Good | 128K | ❌ | Code optimization, refactoring, algorithmic tasks |
| Claude Sonnet 3.5 | 1x | Moderate | Excellent | Excellent | 200K | ✅ | Code generation, long context, balanced reasoning |
| Claude Sonnet 4 | 1x | Moderate | Excellent | Advanced | 200K | ❌ | Complex code, robust reasoning, enterprise tasks |
| Claude Sonnet 4.5 | 1x | Moderate | Excellent | Expert | 200K | ✅ | Advanced code, architecture, design patterns |
| Claude Opus 4.1 | 10x | Slow | Outstanding | Expert | 1M | ✅ | Large codebases, architectural review, research |
| Gemini 2.5 Pro | 1x | Moderate | Excellent | Advanced | 2M | ✅ | Very long context, multi-modal, real-time data |
| Gemini 2.0 Flash (dep.) | 0.25x | Fastest | Good | Good | 1M | ❌ | Fast responses, cost-effective (deprecated) |
| Grok Code Fast 1 | 0.25x | Fastest | Good | Basic | 128K | ❌ | Speed-critical simple tasks, preview (free) |
| o3 (deprecated) | 1x | Slow | Good | Expert | 128K | ❌ | Advanced reasoning, algorithmic optimization |
| o4-mini (deprecated) | 0.33x | Fast | Good | Good | 128K | ❌ | Reasoning at lower cost (deprecated) |
#### Selection Decision Tree
```
START
│
├─ Task Complexity?
│ ├─ Simple/Repetitive → GPT-5 mini, Grok Code Fast 1, GPT-4.1
│ ├─ Moderate → GPT-4.1, Claude Sonnet 4, GPT-5
│ └─ Complex/Advanced → Claude Sonnet 4.5, GPT-5, Gemini 2.5 Pro, Claude Opus 4.1
│
├─ Reasoning Depth?
│ ├─ Basic → GPT-5 mini, Grok Code Fast 1
│ ├─ Intermediate → GPT-4.1, Claude Sonnet 4
│ ├─ Advanced → GPT-5, Claude Sonnet 4.5
│ └─ Expert → Claude Opus 4.1, o3 (deprecated)
│
├─ Code-Specific?
│ ├─ Yes → GPT-5 Codex, Claude Sonnet 4.5, GPT-5
│ └─ No → GPT-5, Claude Sonnet 4
│
├─ Context Size?
│ ├─ Small (<50K tokens) → Any model
│ ├─ Medium (50-200K) → Claude models, GPT-5, Gemini
│ ├─ Large (200K-1M) → Gemini 2.5 Pro, Claude Opus 4.1
│ └─ Very Large (>1M) → Gemini 2.5 Pro (2M), Claude Opus 4.1 (1M)
│
├─ Vision Required?
│ ├─ Yes → GPT-4.1, GPT-5, Claude Sonnet 3.5/4.5, Gemini 2.5 Pro, Claude Opus 4.1
│ └─ No → All models
│
├─ Cost Sensitivity? (based on subscriptionTier)
│ ├─ Free Tier → 0x models only: GPT-4.1, GPT-5 mini, Grok Code Fast 1
│ ├─ Pro (1000 premium/month) → Prioritize 0x, use 1x judiciously, avoid 10x
│ └─ Pro+ (5000 premium/month) → 1x freely, 10x for critical tasks
│
└─ Priority Factor?
├─ Speed → GPT-5 mini, Grok Code Fast 1, Gemini 2.0 Flash
├─ Cost → 0x models (GPT-4.1, GPT-5 mini) or lower multipliers (0.25x, 0.33x)
├─ Quality → Claude Sonnet 4.5, GPT-5, Claude Opus 4.1
└─ Balanced → GPT-4.1, Claude Sonnet 4, GPT-5
```
### 3. Recommendation Generation Phase
**Primary Recommendation**:
Identify the single best model based on task analysis and decision tree
Provide specific rationale tied to file content characteristics
Explain multiplier cost implications for user's subscription tier
**Alternative Recommendations**:
Suggest 1-2 alternative models with trade-off explanations
Include scenarios where alternatives might be preferred
Consider priority factor overrides (speed vs. quality vs. cost)
**Auto-Selection Guidance**:
Assess if task is suitable for auto model selection (excludes premium models > 1x)
Explain when manual selection is beneficial vs. letting Copilot choose
Note any limitations of auto-selection for the specific task
**Deprecation Warnings**:
Flag if file currently specifies a deprecated model (o3, o4-mini, Claude Sonnet 3.7, Gemini 2.0 Flash)
Provide migration path to recommended replacement
Include timeline for deprecation (e.g., "o3 deprecating 2025-10-23")
**Subscription Tier Considerations**:
**Free Tier**: Recommend only 0x multiplier models (GPT-4.1, GPT-5 mini, Grok Code Fast 1)
**Pro Tier**: Balance between 0x (unlimited) and 1x (1000/month) models
**Pro+ Tier**: More freedom with 1x models (5000/month), justify 10x usage for exceptional cases
### 4. Integration Recommendations
**Frontmatter Update Guidance**:
If file does not specify a `model` field:
```markdown
SynapticSkills