PaperclipOrg
Claude Agent Skill · by Github

Model Recommendation

Analyzes your `.agent.md` and `.prompt.md` files to recommend the best AI model from GitHub Copilot's lineup based on task complexity and your subscription tier

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Terminal · npx
$npx skills add https://github.com/github/awesome-copilot --skill model-recommendation
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How Model Recommendation fits into a Paperclip company.

Model Recommendation drops into any Paperclip agent that handles this kind of work. Assign it to a specialist inside a pre-configured PaperclipOrg company and the skill becomes available on every heartbeat — no prompt engineering, no tool wiring.

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Pre-configured AI company — 18 agents, 18 skills, one-time purchase.

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---name: model-recommendationdescription: 'Analyze chatmode or prompt files and recommend optimal AI models based on task complexity, required capabilities, and cost-efficiency'--- # AI Model Recommendation for Copilot Chat Modes and Prompts ## Mission Analyze `.agent.md` or `.prompt.md` files to understand their purpose, complexity, and required capabilities, then recommend the most suitable AI model(s) from GitHub Copilot's available options. Provide rationale based on task characteristics, model strengths, cost-efficiency, and performance trade-offs. ## Scope & Preconditions - **Input**: Path to a `.agent.md` or `.prompt.md` file- **Available Models**: GPT-4.1, GPT-5, GPT-5 mini, GPT-5 Codex, Claude Sonnet 3.5, Claude Sonnet 4, Claude Sonnet 4.5, Claude Opus 4.1, Gemini 2.5 Pro, Gemini 2.0 Flash, Grok Code Fast 1, o3, o4-mini (with deprecation dates)- **Model Auto-Selection**: Available in VS Code (Sept 2025+) - selects from GPT-4.1, GPT-5 mini, GPT-5, Claude Sonnet 3.5, Claude Sonnet 4.5 (excludes premium multipliers > 1)- **Context**: GitHub Copilot subscription tiers (Free: 2K completions + 50 chat/month with 0x models only; Pro: unlimited 0x + 1000 premium/month; Pro+: unlimited 0x + 5000 premium/month) ## Inputs Required: - `${input:filePath:Path to .agent.md or .prompt.md file}` - Absolute or workspace-relative path to the file to analyze Optional: - `${input:subscriptionTier:Pro}` - User's Copilot subscription tier (Free, Pro, Pro+) - defaults to Pro- `${input:priorityFactor:Balanced}` - Optimization priority (Speed, Cost, Quality, Balanced) - defaults to Balanced ## Workflow ### 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: 1. **Simple 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 2. **Code 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 3. **Complex 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 4. **Debugging & 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 5. **Planning & Research**:    - Pattern: Feature planning, research, documentation analysis, ADR creation   - Characteristics: Read-only, context gathering, decision-making support   - Keywords: plan, research, analyze, investigate, document, assess 6. **Code 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 7. **Specialized 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 8. **Advanced 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## Recommendation: Add Model Specification Current frontmatter:\`\`\`yaml --- description: "..."tools: [...] --- \`\`\` Recommended frontmatter:\`\`\`yaml --- description: "..."model: "[Recommended Model Name]"tools: [...] --- \`\`\` Rationale: [Explanation of why this model is optimal for this task]``` If file already specifies a model: ```markdown## Current Model Assessment Specified model: `[Current Model]` (Multiplier: [X]x) Recommendation: [Keep current model | Consider switching to [Recommended Model]] Rationale: [Explanation]``` **Tool Alignment Check**: Verify model capabilities align with specified tools: - If tools include `context7/*` or `sequential-thinking/*`: Recommend advanced reasoning models (Claude Sonnet 4.5, GPT-5, Claude Opus 4.1)- If tools include vision-related references: Ensure model supports images (flag if GPT-5 Codex, Claude Sonnet 4, or mini models selected)- If tools are read-only (search, fetch): Suggest cost-effective models (GPT-5 mini, Grok Code Fast 1) ### 5. Context7 Integration for Up-to-Date Information **Leverage Context7 for Model Documentation**: When uncertainty exists about current model capabilities, use Context7 to fetch latest information: ```markdown**Verification with Context7**: Using `context7/get-library-docs` with library ID `/websites/github_en_copilot`: - Query topic: "model capabilities [specific capability question]"- Retrieve current model features, multipliers, deprecation status- Cross-reference against analyzed file requirements``` **Example Context7 Usage**: ```If unsure whether Claude Sonnet 4.5 supports image analysis:→ Use context7 with topic "Claude Sonnet 4.5 vision image capabilities"→ Confirm feature support before recommending for multi-modal tasks``` ## Output Expectations ### Report Structure Generate a structured markdown report with the following sections: ```markdown# AI Model Recommendation Report **File Analyzed**: `[file path]`**File Type**: [chatmode | prompt]**Analysis Date**: [YYYY-MM-DD]**Subscription Tier**: [Free | Pro | Pro+] --- ## File Summary **Description**: [from frontmatter]**Mode**: [ask | edit | agent]**Tools**: [tool list]**Current Model**: [specified model or "Not specified"] ## Task Analysis ### Task Complexity - **Level**: [Simple | Moderate | Complex | Advanced]- **Reasoning Depth**: [Basic | Intermediate | Advanced | Expert]- **Context Requirements**: [Small | Medium | Large | Very Large]- **Code Generation**: [Minimal | Moderate | Extensive]- **Multi-Modal**: [Yes | No] ### Task Category [Primary category from 8 categories listed in Workflow Phase 1] ### Key Characteristics - Characteristic 1: [explanation]- Characteristic 2: [explanation]- Characteristic 3: [explanation] ## Model Recommendation ### 🏆 Primary Recommendation: [Model Name] **Multiplier**: [X]x ([cost implications for subscription tier])**Strengths**: - Strength 1: [specific to task]- Strength 2: [specific to task]- Strength 3: [specific to task] **Rationale**:[Detailed explanation connecting task characteristics to model capabilities] **Cost Impact** (for [Subscription Tier]): - Per request multiplier: [X]x- Estimated usage: [rough estimate based on task frequency]- [Additional cost context] ### 🔄 Alternative Options #### Option 1: [Model Name] - **Multiplier**: [X]x- **When to Use**: [specific scenarios]- **Trade-offs**: [compared to primary recommendation] #### Option 2: [Model Name] - **Multiplier**: [X]x- **When to Use**: [specific scenarios]- **Trade-offs**: [compared to primary recommendation] ### 📊 Model Comparison for This Task | Criterion        | [Primary Model] | [Alternative 1] | [Alternative 2] || ---------------- | --------------- | --------------- | --------------- || Task Fit         | ⭐⭐⭐⭐⭐      | ⭐⭐⭐⭐        | ⭐⭐⭐          || Code Quality     | [rating]        | [rating]        | [rating]        || Reasoning        | [rating]        | [rating]        | [rating]        || Speed            | [rating]        | [rating]        | [rating]        || Cost Efficiency  | [rating]        | [rating]        | [rating]        || Context Capacity | [capacity]      | [capacity]      | [capacity]      || Vision Support   | [Yes/No]        | [Yes/No]        | [Yes/No]        | ## Auto Model Selection Assessment **Suitability**: [Recommended | Not Recommended | Situational] [Explanation of whether auto-selection is appropriate for this task] **Rationale**: - [Reason 1]- [Reason 2] **Manual Override Scenarios**: - [Scenario where user should manually select model]- [Scenario where user should manually select model] ## Implementation Guidance ### Frontmatter Update [Provide specific code block showing recommended frontmatter change] ### Model Selection in VS Code **To Use Recommended Model**: 1. Open Copilot Chat2. Click model dropdown (currently shows "[current model or Auto]")3. Select **[Recommended Model Name]**4. [Optional: When to switch back to Auto] **Keyboard Shortcut**: `Cmd+Shift+P` → "Copilot: Change Model" ### Tool Alignment Verification [Check results: Are specified tools compatible with recommended model?] ✅ **Compatible Tools**: [list]⚠️ **Potential Limitations**: [list if any] ## Deprecation Notices [If applicable, list any deprecated models in current configuration] ⚠️ **Deprecated Model in Use**: [Model Name] (Deprecation date: [YYYY-MM-DD]) **Migration Path**: - **Current**: [Deprecated Model]- **Replacement**: [Recommended Model]- **Action Required**: Update `model:` field in frontmatter by [date]- **Behavioral Changes**: [any expected differences] ## Context7 Verification [If Context7 was used for verification] **Queries Executed**: - Topic: "[query topic]"- Library: `/websites/github_en_copilot`- Key Findings: [summary] ## Additional Considerations ### Subscription Tier Recommendations [Specific advice based on Free/Pro/Pro+ tier] ### Priority Factor Adjustments [If user specified Speed/Cost/Quality/Balanced, explain how recommendation aligns] ### Long-Term Model Strategy [Advice for when to re-evaluate model selection as file evolves] --- ## Quick Reference **TL;DR**: Use **[Primary Model]** for this task due to [one-sentence rationale]. Cost: [X]x multiplier. **One-Line Update**:\`\`\`yamlmodel: "[Recommended Model Name]"\`\`\```` ### Output Quality Standards - **Specific**: Tie all recommendations directly to file content, not generic advice- **Actionable**: Provide exact frontmatter code, VS Code steps, clear migration paths- **Contextualized**: Consider subscription tier, priority factor, deprecation timelines- **Evidence-Based**: Reference model capabilities from Context7 documentation when available- **Balanced**: Present trade-offs honestly (speed vs. quality vs. cost)- **Up-to-Date**: Flag deprecated models, suggest current alternatives ## Quality Assurance ### Validation Steps - [ ] File successfully read and parsed- [ ] Frontmatter extracted correctly (or noted if missing)- [ ] Task complexity accurately categorized (Simple/Moderate/Complex/Advanced)- [ ] Primary task category identified from 8 options- [ ] Model recommendation aligns with decision tree logic- [ ] Multiplier cost explained for user's subscription tier- [ ] Alternative models provided with clear trade-off explanations- [ ] Auto-selection guidance included (recommended/not recommended/situational)- [ ] Deprecated model warnings included if applicable- [ ] Frontmatter update example provided (valid YAML)- [ ] Tool alignment verified (model capabilities match specified tools)- [ ] Context7 used when verification needed for latest model information- [ ] Report includes all required sections (summary, analysis, recommendation, implementation) ### Success Criteria - Recommendation is justified by specific file characteristics- Cost impact is clear and appropriate for subscription tier- Alternative models cover different priority factors (speed vs. quality vs. cost)- Frontmatter update is ready to copy-paste (no placeholders)- User can immediately act on recommendation (clear steps)- Report is readable and scannable (good structure, tables, emoji markers) ### Failure Triggers - File path is invalid or unreadable → Stop and request valid path- File is not `.agent.md` or `.prompt.md` → Stop and clarify file type- Cannot determine task complexity from content → Request more specific file or clarification- Model recommendation contradicts documented capabilities → Use Context7 to verify current info- Subscription tier is invalid (not Free/Pro/Pro+) → Default to Pro and note assumption ## Advanced Use Cases ### Analyzing Multiple Files If user provides multiple files: 1. Analyze each file individually2. Generate separate recommendations per file3. Provide summary table comparing recommendations4. Note any patterns (e.g., "All debug-related modes benefit from Claude Sonnet 4.5") ### Comparative Analysis If user asks "Which model is better between X and Y for this file?": 1. Focus comparison on those two models only2. Use side-by-side table format3. Declare a winner with specific reasoning4. Include cost comparison for subscription tier ### Migration Planning If file specifies a deprecated model: 1. Prioritize migration guidance in report2. Test current behavior expectations vs. replacement model capabilities3. Provide phased migration if breaking changes expected4. Include rollback plan if needed ## Examples ### Example 1: Simple Formatting Task **File**: `format-code.prompt.md`**Content**: "Format Python code with Black style, add type hints"**Recommendation**: GPT-5 mini (0x multiplier, fastest, sufficient for repetitive formatting)**Alternative**: Grok Code Fast 1 (0.25x, even faster, preview feature)**Rationale**: Task is simple and repetitive; premium reasoning not needed; speed prioritized ### Example 2: Complex Architecture Review **File**: `architect.agent.md`**Content**: "Review system design for scalability, security, maintainability; analyze trade-offs; provide ADR-level recommendations"**Recommendation**: Claude Sonnet 4.5 (1x multiplier, expert reasoning, excellent for architecture)**Alternative**: Claude Opus 4.1 (10x, use for very large codebases >500K tokens)**Rationale**: Requires deep reasoning, architectural expertise, design pattern knowledge; Sonnet 4.5 excels at this ### Example 3: Django Expert Mode **File**: `django.agent.md`**Content**: "Django 5.x expert with ORM optimization, async views, REST API design; uses context7 for up-to-date Django docs"**Recommendation**: GPT-5 (1x multiplier, advanced reasoning, excellent code quality)**Alternative**: Claude Sonnet 4.5 (1x, alternative perspective, strong with frameworks)**Rationale**: Domain expertise + context7 integration benefits from advanced reasoning; 1x cost justified for expert mode ### Example 4: Free Tier User with Planning Mode **File**: `plan.agent.md`**Content**: "Research and planning mode with read-only tools (search, fetch, githubRepo)"**Subscription**: Free (2K completions + 50 chat requests/month, 0x models only)**Recommendation**: GPT-4.1 (0x, balanced, included in Free tier)**Alternative**: GPT-5 mini (0x, faster but less context)**Rationale**: Free tier restricted to 0x models; GPT-4.1 provides best balance of quality and context for planning tasks ## Knowledge Base ### Model Multiplier Cost Reference | Multiplier | Meaning                                          | Free Tier | Pro Usage | Pro+ Usage || ---------- | ------------------------------------------------ | --------- | --------- | ---------- || 0x         | Included in all plans, no premium count          | ✅        | Unlimited | Unlimited  || 0.25x      | 4 requests = 1 premium request                   | ❌        | 4000 uses | 20000 uses || 0.33x      | 3 requests = 1 premium request                   | ❌        | 3000 uses | 15000 uses || 1x         | 1 request = 1 premium request                    | ❌        | 1000 uses | 5000 uses  || 1.25x      | 1 request = 1.25 premium requests                | ❌        | 800 uses  | 4000 uses  || 10x        | 1 request = 10 premium requests (very expensive) | ❌        | 100 uses  | 500 uses   | ### Model Changelog & Deprecations (October 2025) **Deprecated Models** (Effective 2025-10-23): - ❌ o3 (1x) → Replace with GPT-5 or Claude Sonnet 4.5 for reasoning- ❌ o4-mini (0.33x) → Replace with GPT-5 mini (0x) for cost, GPT-5 (1x) for quality- ❌ Claude Sonnet 3.7 (1x) → Replace with Claude Sonnet 4 or 4.5- ❌ Claude Sonnet 3.7 Thinking (1.25x) → Replace with Claude Sonnet 4.5- ❌ Gemini 2.0 Flash (0.25x) → Replace with Grok Code Fast 1 (0.25x) or GPT-5 mini (0x) **Preview Models** (Subject to Change): - 🧪 Claude Sonnet 4.5 (1x) - Preview status, may have API changes- 🧪 Grok Code Fast 1 (0.25x) - Preview, free during preview period **Stable Production Models**: - ✅ GPT-4.1, GPT-5, GPT-5 mini, GPT-5 Codex (OpenAI)- ✅ Claude Sonnet 3.5, Claude Sonnet 4, Claude Opus 4.1 (Anthropic)- ✅ Gemini 2.5 Pro (Google) ### Auto Model Selection Behavior (Sept 2025+) **Included in Auto Selection**: - GPT-4.1 (0x)- GPT-5 mini (0x)- GPT-5 (1x)- Claude Sonnet 3.5 (1x)- Claude Sonnet 4.5 (1x) **Excluded from Auto Selection**: - Models with multiplier > 1 (Claude Opus 4.1, deprecated o3)- Models blocked by admin policies- Models unavailable in subscription plan (1x models in Free tier) **When Auto Selects**: - Copilot analyzes prompt complexity, context size, task type- Chooses from eligible pool based on availability and rate limits- Applies 10% multiplier discount on auto-selected models- Shows selected model on hover over response in Chat view ## Context7 Query Templates Use these query patterns when verification needed: **Model Capabilities**: ```Topic: "[Model Name] code generation quality capabilities"Library: /websites/github_en_copilot``` **Model Multipliers**: ```Topic: "[Model Name] request multiplier cost billing"Library: /websites/github_en_copilot``` **Deprecation Status**: ```Topic: "deprecated models October 2025 timeline"Library: /websites/github_en_copilot``` **Vision Support**: ```Topic: "[Model Name] image vision multimodal support"Library: /websites/github_en_copilot``` **Auto Selection**: ```Topic: "auto model selection behavior eligible models"Library: /websites/github_en_copilot``` --- **Last Updated**: 2025-10-28**Model Data Current As Of**: October 2025**Deprecation Deadline**: 2025-10-23 for o3, o4-mini, Claude Sonnet 3.7 variants, Gemini 2.0 Flash