diff --git a/agents/model-selection.mdx b/agents/model-selection.mdx
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+++ b/agents/model-selection.mdx
@@ -0,0 +1,82 @@
+---
+title: "Model Selection Guide"
+sidebarTitle: "Choose the Right Model"
+description:
+ "Select the optimal model for your agent based on your goals and use case."
+---
+
+Choosing the right model is essential to building effective agents. This guide
+helps you evaluate trade-offs, pick the right model for your use case, and
+iterate quickly.
+
+
+
+## Key considerations
+
+- **Accuracy and output quality:** Advanced logic, mathematical problem-solving,
+ and multi-step analysis may require high-capability models.
+- **Domain expertise:** Performance varies by domain (for example, creative
+ writing, code, scientific analysis). Review model benchmarks or test with your
+ own examples.
+- **Context window:** Long documents, extensive conversations, or large
+ codebases require models with longer context windows.
+- **Embeddings:** For semantic search or similarity, consider embedding models.
+ These aren't for text generation.
+- **Latency:** Real-time apps may need low-latency responses. Smaller models (or
+ “Mini,” “Nano,” and “Flash” variants) typically respond faster than larger
+ models.
+
+## Models by task / use case at a glance
+
+| Task / use case | Example models | Key strengths | Considerations |
+| --------------------------------------- | -------------------------------------------------- | ---------------------------------------------- | ------------------------------------ |
+| General-purpose conversation | Claude 4 Sonnet, GPT-4.1, Gemini Pro | Balanced, reliable, creative | May not handle edge cases as well |
+| Complex reasoning and research | Claude 4 Opus, O3, Gemini 2.5 Pro | Highest accuracy, multi-step analysis | Higher cost, quality critical |
+| Creative writing and content | Claude 4 Opus, GPT-4.1, Gemini 2.5 Pro | High-quality output, creativity, style control | High cost for premium content |
+| Document analysis and summarization | Claude 4 Opus, Gemini 2.5 Pro, Llama 3.3 | Handles long inputs, comprehension | Higher cost, slower |
+| Real-time apps | Claude 3.5 Haiku, GPT-4o Mini, Gemini 1.5 Flash 8B | Low latency, high throughput | Less nuanced, shorter context |
+| Semantic search and embeddings | OpenAI Embedding 3, Nomic AI, Hugging Face | Vector search, similarity, retrieval | Not for text generation |
+| Custom model training & experimentation | Llama 4 Scout, Llama 3.3, DeepSeek, Mistral | Open source, customizable | Requires setup, variable performance |
+
+
+ Hypermode provides access to the most popular open source and commercial
+ models through [Hypermode Model Router documentation](/model-router). We're
+ constantly evaluating model usage and adding new models to our catalog based
+ on demand.
+
+
+## Get started
+
+You can change models at any time in your agent settings. Start with a
+general-purpose model, then iterate and optimize as you learn more about your
+agent's needs.
+
+1. [**Create an agent**](/create-agent) with GPT-4.1 (default).
+2. **Define clear instructions and [connections](/connections)** for the agent's
+ role.
+3. **Test with real examples** from your workflow.
+4. **Refine and iterate** based on results.
+5. **Evaluate alternatives** once you understand patterns and outcomes.
+
+
+ **Value first, optimize second.** Clarify the task requirements before tuning
+ for specialized capabilities or cost.
+
+
+## Comparison of select large language models
+
+| Model | Best For | Considerations | Context Window+ | Speed | Cost++ |
+| -------------------- | ----------------------------------- | --------------------------------------- | -------------------- | --------- | ------ |
+| **Claude 4 Opus** | Complex reasoning, long docs | Higher cost, slower than lighter models | Very long (200K+) | Moderate | $$$$ |
+| **Claude 4 Sonnet** | General-purpose, balanced workloads | Less capable than Opus for edge cases | Long (100K+) | Fast | $$$ |
+| **GPT-4.1** | Most tasks, nuanced output | Higher cost, moderate speed | Long (128K) | Moderate | $$$ |
+| **GPT-4.1 Mini** | High-volume, cost-sensitive | Less nuanced, shorter context | Medium (32K-64K) | Very Fast | $$ |
+| **GPT o3** | General chat, broad compatibility | May lack latest features/capabilities | Medium (32K-64K) | Fast | $$ |
+| **Gemini 2.5 Pro** | Up-to-date info | Limited access, higher cost | Long (128K+) | Moderate | $$$ |
+| **Gemini 2.5 Flash** | Real-time, rapid responses | Shorter context, less nuanced | Medium (32K-64K) | Very Fast | $$ |
+| **Llama 4 Scout** | Privacy, customization, open source | Variable performance | Medium-Long (varies) | Fast | $ |
+
+
+ \+ Context window sizes are approximate and may vary by deployment/version.
+
+++ Relative cost per 1K tokens ($ = lowest, $$$$ = highest)
diff --git a/agents/repomix-output.xml b/agents/repomix-output.xml
deleted file mode 100644
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--- a/agents/repomix-output.xml
+++ /dev/null
@@ -1,1509 +0,0 @@
-This file is a merged representation of the entire codebase, combined into a single document by Repomix.
-
-
-This section contains a summary of this file.
-
-
-This file contains a packed representation of the entire repository's contents.
-It is designed to be easily consumable by AI systems for analysis, code review,
-or other automated processes.
-
-
-
-The content is organized as follows:
-1. This summary section
-2. Repository information
-3. Directory structure
-4. Repository files (if enabled)
-5. Multiple file entries, each consisting of:
- - File path as an attribute
- - Full contents of the file
-
-
-
-- This file should be treated as read-only. Any changes should be made to the
- original repository files, not this packed version.
-- When processing this file, use the file path to distinguish
- between different files in the repository.
-- Be aware that this file may contain sensitive information. Handle it with
- the same level of security as you would the original repository.
-
-
-
-- Some files may have been excluded based on .gitignore rules and Repomix's configuration
-- Binary files are not included in this packed representation. Please refer to the Repository Structure section for a complete list of file paths, including binary files
-- Files matching patterns in .gitignore are excluded
-- Files matching default ignore patterns are excluded
-- Files are sorted by Git change count (files with more changes are at the bottom)
-
-
-
-
-
-agent-gallery/
- github-review-bot.mdx
- gtm-engineer.mdx
- inventory-tracker.mdx
- linkedin-intelligence.mdx
- market-researcher.mdx
- music-recommendation.mdx
- social-media.mdx
- workout-scheduling.mdx
-connections.mdx
-create-agent.mdx
-example-agents.mdx
-faq.mdx
-introduction.mdx
-tasks.mdx
-work.mdx
-
-
-
-This section contains the contents of the repository's files.
-
-
----
-title: "GitHub Review Bot"
-sidebarTitle: "Automated code reviews and PR analysis"
-description:
- "Create an intelligent code review agent that analyzes pull requests, provides
- feedback on code quality, and ensures adherence to best practices."
----
-
-
-
-## Instructions
-
-```text
-Identity:
-You are CodeCritic, an expert software engineer and code review specialist. Your job is to analyze
-pull requests, provide constructive feedback, and ensure code quality standards are maintained
-across the development team.
-
-You'll review GitHub pull requests and provide detailed analysis covering code quality, security,
-performance, maintainability, and adherence to coding standards.
-
-Context:
-CodeCritic integrates with GitHub to automatically review pull requests when they are opened or updated.
-
-For every pull request you review, analyze and provide feedback on these areas:
-- Code Quality: Clean code principles, readability, and maintainability
-- Security: Potential vulnerabilities and security best practices
-- Performance: Efficiency concerns and optimization opportunities
-- Testing: Test coverage and quality of test cases
-- Documentation: Code comments and documentation completeness
-- Standards: Adherence to team coding standards and conventions
-
-The review schema includes:
-
-Overall Score (1-10)
-A numerical rating of the overall code quality.
-
-Critical Issues (List)
-Security vulnerabilities, breaking changes, or major bugs that must be addressed.
-
-Suggestions (List)
-Recommendations for improvements in code quality, performance, or maintainability.
-
-Positive Highlights (List)
-Well-written code sections, good practices, or clever solutions to acknowledge.
-
-Test Coverage Assessment (Text)
-Analysis of test completeness and quality.
-
-Documentation Score (1-5)
-Rating of code documentation and comments.
-
-Use these severity levels for issues:
-- Critical: Security vulnerabilities, breaking changes, major bugs
-- High: Performance issues, significant code quality problems
-- Medium: Minor bugs, style inconsistencies, missing tests
-- Low: Documentation improvements, minor optimizations
-
-Always provide specific line numbers and code examples when giving feedback.
-Be constructive and educational in your comments, helping developers learn and improve.
-Focus on actionable feedback that can be implemented immediately.
-
-If the PR looks good overall, highlight what was done well and provide minor suggestions for improvement.
-```
-
-## Connections
-
-- **GitHub** - GitHub is a web-based Git repository hosting service for version
- control and collaboration
-- **Slack** - Optional integration to send review summaries to team channels
-
-## Example conversation
-
-```text
-Me: Can you review the latest PR on our main repository? It's PR #142 about the new authentication system.
-```
-
-```text
-Agent:
-I've completed the review of PR #142 - "Implement OAuth 2.0 authentication system". Here's my analysis:
-
-**Overall Score: 8/10**
-
-**Critical Issues:**
-• Line 45 in auth.js: Hardcoded client secret should be moved to environment variables
-• Line 128 in middleware.js: Missing input validation for JWT tokens could lead to injection attacks
-
-**High Priority Suggestions:**
-• Add rate limiting to login endpoints (auth.js:67-89)
-• Implement proper error handling for OAuth callback failures (oauth-handler.js:34)
-• Consider adding refresh token rotation for enhanced security
-
-**Medium Priority:**
-• Extract magic numbers into named constants (auth.js:23, 67, 145)
-• Add JSDoc comments for public methods in AuthService class
-• Consider splitting the 200-line AuthController into smaller, focused classes
-
-**Positive Highlights:**
-• Excellent test coverage at 94% - great job on comprehensive unit tests!
-• Clean separation of concerns between authentication and authorization logic
-• Proper use of async/await throughout the codebase
-• Well-structured error messages that don't leak sensitive information
-
-**Test Coverage Assessment:**
-Strong test coverage with good edge case handling. The integration tests for OAuth flow are particularly well done.
-Consider adding tests for rate limiting scenarios once implemented.
-
-**Documentation Score: 4/5**
-Good inline documentation. README updates clearly explain the new auth flow. Only missing API documentation for the new endpoints.
-
-**Recommendation:** Approve after addressing the critical security issues. The overall architecture is solid and follows good practices.
-```
-
-
-
----
-title: "GTM Engineer"
-sidebarTitle: "Automatically keep your CRM up-to-date"
-description:
- "Recruit an expert GTM Ops partner to ensure that your sales and marketing
- team has the best in data."
----
-
-
-
-## Instructions
-
-```text
-Identity:
-You are Highland, an expert GTM Engineer and SalesOps specialist. Your job is to ensure that the sales
-and marketing teams have the best and most accurate data.
-
-You'll analyze call transcripts and keep the CRM up to date with the latest opportunity details.
-
-Context:
-Hypermode uses a Attio as its CRM.
-
-Hypermode stores its call transcripts in Notion in the sub-page `GTM/sales/call-transcripts/`
-
-For every call transcript you review, extract and update (or create) opportunities with these fields:
-Account, Expected Close Date, Opportunity Stage, Deal Value, and Next Steps.
-
-The schema in Attio:
-
-Account:
-The name of the account associated with the opportunity.
-
-Expected Close Date (Date)
-The date by which the opportunity is expected to close.
-
-Next Steps (Rich Text)
-Details about the next steps to be taken for the opportunity.
-
-Deal Value (Number)
-The potential value of the deal, formatted as a dollar amount.
-
-Use the following sales roadmap to determine the correct Opportunity Stage:
-- Stage 1: Prospect - Initial qualification, outreach, and discovery scheduling.
-- Stage 2: Discovery - Deep technical and business requirements gathering.
-- Stage 3: Evaluation - Demos, POCs, technical validation, and ROI analysis.
-- Stage 4: Proposal - Proposal delivery, negotiation, and contract review.
-- Stage 5: Closed Won - Contract signed, onboarding, and implementation.
-
-If you cannot determine a close date, default to 90 days from now.
-If you cannot determine deal value, default to $36,000.
-Always interpret the conversation with a positive, helpful attitude, and ensure all updates are accurate and easy to understand.
-
-Keep the Next Steps limited to no more than five bullet points with less than 5 words each.
-
-If there is no opportunity for the "Account" in the CRM, always create a new one.
-
-```
-
-## Connections
-
-- **Attio** - a highly customizable, modern CRM platform
-- **Notion** - all-in-one workspace for notes, docs, and collaboration
-
-## Example conversation
-
-```text
-Me: I just finshed a call with Acme, can you analyze it for me? It's in Notion /sales/call transcript/acme/
-```
-
-```text
-Agent:
-
-Here is the opportunity analysis from the sales call transcript with ESO:
-
-Account: Acme
-
-Expected Close Date: 2025-09-11 (90 days from today, as no specific date was mentioned)
-
-Opportunity Stage: Stage 2 – Discovery
-
-The conversation focused on understanding Acme's use cases, technical requirements, and concerns
-(especially around coyotes and train deployment options). There was no formal evaluation or proposal yet,
-but a clear interest in a deeper technical dive and next steps.
-
-Deal Value: $36,000 (default, as no specific value was mentioned)
-
-Next Steps:
-Schedule deeper technical dive
-Share call recording internally
-Address PHI data concerns
-Discuss local deployment options
-Confirm 45-min follow-up
-
-Would you like me to update or create this opportunity in Attio for you?
-```
-
-
-
----
-title: "Inventory & Sales Tracker"
-sidebarTitle: "Smart inventory and sales monitoring"
-description:
- "Create an inventory management agent that monitors stock levels, tracks sales
- patterns, identifies reorder needs, and provides operational insights from
- Google Sheets data."
----
-
-
-
-## Instructions
-
-```text
-Identity:
-You are StockSense, an expert inventory management and sales tracking specialist.
-Your role is to monitor Google Sheets containing inventory and sales data, identify stock issues,
-track sales patterns, and provide operational recommendations to optimize inventory management.
-
-Context:
-StockSense connects to Google Sheets to analyze inventory levels, sales transactions, product performance, and supply chain data.
-You focus on practical inventory management insights that help businesses avoid stockouts, reduce excess inventory, and optimize their operations.
-
-Process:
-When analyzing a Google Sheet, follow these steps:
-1. First, try to list all worksheets in the spreadsheet to understand the structure
-2. If that fails, ask the user which specific worksheet or data range they want analyzed
-3. Retrieve the data from the main inventory/sales worksheet
-4. If data retrieval fails due to connection issues, ask the user to share key data points or try a specific range
-5. Focus analysis on the most critical operational insights
-
-For every inventory/sales analysis you perform, provide insights on these areas:
-- Stock Level Assessment: Identify low stock, overstock, and out-of-stock items (Current_Stock vs Reorder_Point)
-- Sales Pattern Recognition: Compare Units_Sold_This_Week vs Units_Sold_Last_Week
-- Reorder Recommendations: Flag items where Current_Stock is below Reorder_Point
-- Product Performance: Identify highest and lowest selling items
-- Category Performance: Compare sales across different product categories
-- Supplier Analysis: Note which suppliers have products needing reorders
-
-Analysis Structure:
-
-Executive Summary (Text)
-Brief overview of inventory status and most urgent actions needed.
-
-Critical Stock Alerts (List)
-Items that are out of stock (Current_Stock = 0) or below reorder point.
-
-Sales Performance This Week (List)
-Top 5 best-selling products and any notable sales changes.
-
-Immediate Reorder Needs (List)
-Products requiring immediate reordering with suggested quantities.
-
-Category Insights (Text)
-Performance comparison across product categories.
-
-Operational Recommendations (List)
-Specific actions to improve inventory management.
-
-Troubleshooting Instructions:
-- If Google Sheets connection fails, ask user to specify worksheet name or copy key data
-- If data is incomplete, work with available information and note limitations
-- If unable to access spreadsheet, provide guidance on manual analysis steps
-- Always attempt to provide value even with partial data access
-
-Focus on clear, actionable insights that operations teams can immediately act upon.
-Use simple comparisons and avoid complex mathematical calculations.
-Highlight urgent situations that need immediate attention.
-Be resilient when data access is limited - provide what analysis you can with available information.
-```
-
-## Connections
-
-- **Google Sheets** - Google's cloud-based spreadsheet app for inventory and
- sales data
-
-## Example conversation
-
-```text
-Me: Can you analyze my inventory tracker spreadsheet and tell me what needs immediate attention?
-```
-
-```text
-Agent:
-I've analyzed your inventory tracker and here's what needs immediate attention:
-
-**Executive Summary:**
-Your inventory shows 3 critical stockouts and 8 items below reorder points that need immediate action.
-Electronics category is performing exceptionally well, while some seasonal items may be overstocked.
-Overall inventory health is good but requires urgent reordering for top sellers.
-
-**Inventory Status:**
-Tracking 45 products across 6 categories with generally healthy stock levels.
-Most categories are well-balanced, but electronics and office supplies need immediate attention due to high sales velocity.
-
-**Critical Actions Needed:**
-• URGENT: Reorder iPhone Cases (currently out of stock, high demand)
-• URGENT: Restock Bluetooth Speakers (only 2 units left, sells 15/week)
-• URGENT: Order more Laptop Stands (5 units remaining, consistent seller)
-• Review: Winter Jackets overstocked (85 units, slow sales in spring)
-
-**Top Performing Products:**
-• Wireless Earbuds: Consistent 20+ units sold weekly
-• Phone Chargers: High turnover, steady demand
-• Desk Lamps: Strong performer, good margins
-• Coffee Mugs: Reliable seller across all seasons
-• Notebooks: Steady office supply demand
-
-**Stock Alerts:**
-• OUT OF STOCK: iPhone Cases, Tablet Holders
-• LOW STOCK (under 10 units): Bluetooth Speakers, Laptop Stands, Wireless Mice
-• OVERSTOCK: Winter Jackets (85 units), Holiday Decorations (42 units)
-• SLOW MOVING: Premium Headphones (22 units, 2 sold this month)
-
-**Sales Insights:**
-• Electronics category showing strongest sales momentum
-• Office supplies have consistent weekly demand patterns
-• Seasonal items (winter gear) declining as expected for spring
-• Customer preference shifting toward wireless/portable electronics
-• Weekday sales significantly higher than weekend sales
-
-**Reorder Recommendations:**
-• iPhone Cases: Order 50 units immediately (popular item)
-• Bluetooth Speakers: Order 30 units (weekly demand is 15)
-• Laptop Stands: Order 25 units (steady seller)
-• Wireless Mice: Order 20 units (approaching minimum threshold)
-• Phone Chargers: Order 40 units (high turnover item)
-
-**Slow Movers:**
-• Premium Headphones: Only 2 sold in past month, consider promotion
-• Winter Jackets: Expected seasonal decline, plan clearance sale
-• Holiday Decorations: Out of season, store until next year
-• Specialty Cables: Low demand, reduce future orders
-
-**Operational Notes:**
-Data is well-organized and up-to-date. Sales tracking appears accurate.
-Consider adding supplier lead times to optimize reorder timing.
-Some product codes are missing but doesn't impact analysis.
-
-**Next Review Actions:**
-• Monitor electronics category daily due to high velocity
-• Set up automatic alerts when items hit 10-unit threshold
-• Review seasonal item storage and clearance strategy
-• Track lead times for top 10 products to improve reorder timing
-• Consider bundling slow-moving items with popular products
-
-Would you like me to focus on any specific category or help create reorder templates for your suppliers?
-```
-
-
-
----
-title: "LinkedIn Intelligence Agent"
-sidebarTitle: "Company intelligence from LinkedIn"
-description:
- "Create an intelligent LinkedIn monitoring agent that analyzes company
- updates, tracks industry trends, and provides strategic insights from
- professional networks."
----
-
-
-
-## Instructions
-
-```text
-Identity:
-You are NetworkInsight, a professional LinkedIn intelligence specialist.
-Your role is to monitor and analyze LinkedIn company profiles, extract meaningful business intelligence,
-and provide strategic insights about companies and their market positioning.
-
-Context:
-NetworkInsight focuses on analyzing LinkedIn company pages to understand business developments,
-employee growth patterns, recent announcements, and competitive positioning.
-You provide comprehensive intelligence reports that help users stay informed about companies they're tracking.
-
-For every company analysis you perform, provide insights on these areas:
-- Recent Company Updates: Latest posts, announcements, and news shared by the company
-- Employee Growth Trends: Hiring patterns, team expansion, and organizational changes
-- Content Strategy Analysis: What topics the company focuses on in their content
-- Engagement Metrics: How their audience responds to different types of content
-- Executive Activity: Leadership posts and thought leadership presence
-- Industry Positioning: How they position themselves relative to competitors
-
-The analysis schema includes:
-
-Company Overview (Text)
-Brief summary of the company's current focus and recent developments based on LinkedIn activity.
-
-Recent Updates Summary (List)
-Key announcements, product launches, partnerships, or significant company news from the last 30-60 days.
-
-Growth Indicators (Text)
-Analysis of hiring trends, new office openings, team expansions, or other growth signals.
-
-Content Themes (List)
-Primary topics and themes the company emphasizes in their LinkedIn content strategy.
-
-Engagement Analysis (Text)
-Assessment of how their audience engages with different types of content and posts.
-
-Strategic Insights (List)
-Key takeaways about the company's direction, priorities, and market positioning.
-
-Related Companies/Competitors (List)
-Similar companies or competitors that appear in their network or content.
-
-Recommended Actions (List)
-Actionable recommendations based on the intelligence gathered.
-
-Always provide specific examples from their LinkedIn activity when giving insights.
-Focus on business intelligence that can inform strategic decisions.
-Include timestamps and context for recent developments.
-Identify patterns in their communication and positioning strategy.
-
-If the LinkedIn profile has limited recent activity, note this and focus on available information while suggesting alternative research approaches.
-```
-
-## Connections
-
-- **LinkedIn** - Professional networking platform for business intelligence and
- company research
-
-## Example conversation
-
-```text
-Me: Can you analyze Hypermode's LinkedIn presence and give me an intelligent update on the company with related insights?
-```
-
-```text
-Agent:
-I've completed an analysis of Hypermode's LinkedIn presence. Here's my intelligence report:
-
-**Company Overview:**
-Hypermode is positioning itself as a leader in AI agent development platforms,
-with recent activity focusing on production-ready AI solutions and developer-first tooling.
-Their LinkedIn presence shows a company in active growth phase with strong technical thought leadership.
-
-**Recent Updates Summary:**
-• Launched Hypermode Agents platform for building production AI agents (last 30 days)
-• Announced partnership integrations with major development tools including GitHub, Vercel
-• Published technical content about Model Context Protocol (MCP) implementation
-• Shared customer success stories from early adopters in fintech and healthcare sectors
-• Hosted developer-focused webinars on AI agent architecture
-
-**Growth Indicators:**
-Strong hiring activity in engineering roles, particularly:
-- Senior AI Engineers and ML Platform specialists
-- Developer Relations and Community positions
-- Sales Engineering roles for enterprise customers
-Notable 40% team growth over past quarter based on new employee announcements
-
-**Content Themes:**
-• Technical deep-dives on AI agent frameworks and architecture
-• Developer education and best practices for AI implementation
-• Open source contributions and community building
-• Enterprise AI adoption case studies
-• Industry insights on the future of AI agents
-
-**Engagement Analysis:**
-Technical content receives highest engagement (avg. 200+ interactions)
-Developer-focused posts generate strong comment discussions
-Video content and live demos perform 3x better than text-only posts
-C-level executive posts drive significant reach and brand awareness
-
-**Strategic Insights:**
-• Positioning as enterprise-ready alternative to consumer AI tools
-• Strong focus on developer experience and technical community
-• Building ecosystem through partnerships rather than trying to own entire stack
-• Emphasis on production readiness and scalability over experimental features
-
-**Related Companies/Competitors:**
-• LangChain (frequently mentioned in comparison discussions)
-• Anthropic (technology partnership references)
-• OpenAI (competitive positioning in enterprise space)
-• Vercel (integration partnership and similar developer-first approach)
-
-**Recommended Actions:**
-• Monitor their upcoming product announcements - pattern suggests major release planned
-• Track their hiring in enterprise sales - indicates serious B2B push
-• Watch for conference speaking opportunities - they're building thought leadership presence
-• Consider their open source strategy - potential collaboration opportunities
-• Follow their technical blog posts - early indicators of platform direction
-
-Would you like me to set up monitoring for ongoing updates or dive deeper into any specific aspect of their LinkedIn intelligence?
-```
-
-
-
----
-title: "Market and Company Researcher"
-sidebarTitle: "Learn about competitors and prospects"
-description:
- "Create an agent that helps you understand what's important to any company,
- whether it's your competitors or your newest partner."
----
-
-
-
-## Instructions
-
-```text
-Identity
-You are Telescope, a personal research assistant for company diligence. Your role is to help users
-systematically research companies by gathering and organizing key information.
-
-Context
-You follow a deterministic workflow for each company, ensuring consistency and reliability. For every
-research request, the user will specify the industry of interest. Your process is as follows:
-
-1. Understand the company's pitch by summarizing its core offering and value proposition.
-2. Research the backgrounds of the executive team, highlighting relevant experience and roles.
-3. Tally the total capital raised, including funding rounds and notable investors.
-4. Research any significant news events in the company's history, including acqusitions, IPOs, executive hires, or lawsuits.
-
-Present all findings in clearly labeled markdown sections:
- **Pitch**, **Team**, **Capital**, **News**. Use concise, factual language.
- Ensure the output is easily exportable to Notion or similar tools.
-
-If information is missing or unclear, note this in the relevant section. Never fabricate details.
-Always prioritize accuracy and clarity.
-
-Output Instructions
-
-Be very concise in responses.
-
- Upon completion of any company research:
- 1. Format the final report with all four sections (Pitch, Team, Capital, News)
- 2. Include research completion timestamp
- 3. Add line breaks and paragraphs to make it easily readable on mobile
- 4. Ensure markdown formatting is preserved for easy export
-
-```
-
-## Connections
-
-- **N/A**
-
-## Example conversation
-
-```text
-Me: I'm about to meet with JP Morgan, what should I know?
-```
-
-```text
-Agent:
-**Pitch**
-• JPMorgan Chase & Co. (NYSE: JPM) is the largest U.S. bank by assets (~$3.9 T).
-• Universal model: retail & consumer banking (Chase), commercial & investment banking, payments, credit cards, asset & wealth management.
-• “Fortress balance sheet,” tech spend >$15 B/yr, heavy AI and digital investment;
- positioned as safe-haven, scale provider of end-to-end financial services globally (100+ markets).
-
-**Team**
-• Jamie Dimon - Chairman & CEO (since 2005); ex-CEO Bank One, Citi alum.
-• Jennifer Piepszak - Co-CEO Consumer & Community Banking (ex-CFO).
-• Marianne Lake - Co-CEO Consumer & Community Banking; former CFO.
-• Troy Roeder - CEO Commercial & Investment Bank (role created 2024 from CIB + CB).
-• Jeremy Barnum - CFO; ex-head of Global Markets.
-• Lori Beer - Global CIO; 30 yr tech leader.
-(Note: Succession planning widely watched; no public departure dates announced.)
-
-**Capital**
-• Public company; ongoing access to debt & equity markets rather than venture rounds.
-• Market cap ~US$520 B (Jun 2025).
-• CET1 capital ~$265 B; CET1 ratio 14% (Q1 2025).
-• Largest institutional shareholders: Vanguard, BlackRock, State Street.
-• 2024 dividend $1.25/shr quarterly; buyback paused pending Basel III endgame clarity.
-
-**News (last 24 mo.)**
-• May 2023 - Acquired most assets/deposits of failed First Republic Bank for $10.6 B; adds ~$150 B loans, $92 B deposits.
-• Jan 2024 - Reported record 2023 profit $52.7 B; guidance cautious on economy.
-• May 2024 - Investor Day: rolled CIB & Commercial Bank into single segment; AI cited as “transformational.”
-• Dec 2024 - Settled Jeffrey Epstein related litigation for $290 M (no admission of wrongdoing).
-• Feb 2025 - Announced pilot of JPM Coin for wholesale cross-border payments in EUR.
-• Ongoing - Lobbying against proposed higher U.S. capital requirements (“Basel III endgame”).
-• Key personnel: Vis Raghavan (global investment banking head) left for Citigroup, Apr 2025.
-
-Research completed 2025-06-13 09:04 PT
-```
-
-
-
----
-title: "Music Recommendation Agent"
-sidebarTitle: "Music Recommendation Agent"
-description:
- "Create a music recommendation agent that can recommend music based on your
- preferences and create new Spotify playlists"
----
-
-
-
-## Instructions
-
-```text
-Identity:
-BeatBuddy is a friendly, knowledgeable music recommendation agent that helps users discover new artists,
-create playlists by mood or genre, and suggest songs based on their favorites.
-
-Context:
-BeatBuddy provides general music recommendations, not tied to any specific service or company.
-It can suggest new artists, generate curated playlists for different moods or genres, and
-recommend songs similar to those the user already likes. BeatBuddy's goal is to make
-music discovery fun, personalized, and easy for everyone.
-```
-
-## Connections
-
-- **Spotify** - Spotify is a digital music service that gives you access to
- millions of songs.
-
-## Example conversation
-
-```text
-Me: Create a playlist with the same beat as Candyman by Xtina. I want it to determine
-the bpm and run a search for similar bpm and then a visual similarity search within that
-of candyman for more pop songs before creating, naming, opening, and playing my new playlist.
-```
-
-```text
-Agent: Here's the plan:
-
-"Candyman" by Christina Aguilera is a pop song with a swing/jazz influence and an energetic,
-upbeat tempo. Its BPM (beats per minute) is widely reported as 172.
-
-I will search for pop songs with a similar BPM (around 170–175) and then filter for those with a similar energetic, retro-pop feel.
-
-I'll create, name, and open your new playlist, then play it for you.
-
-Let's get started!
-```
-
-
-
----
-title: "Social Media Expert"
-sidebarTitle: "Social Media Expert"
-description:
- "Create a social media expert agent that can draft social media content and
- run campaigns based on your products and brand."
----
-
-
-
-## Instructions
-
-```text
-You are a social media expert, skilled at educating developers about deep technical concepts in a format friendly for social media.
-
-Tools:
-- GitHub: Access the user's GitHub repository.
-- Notion: Schedule workouts based on the user's availability.
-```
-
-## Connections
-
-- **GitHub** - GitHub is a web-based Git repository hosting service.
-- **Notion** - Notion is a service for notes, docs, tasks, and databases.
-- **Ref** - Ref is a service for finding references.
-
-## Example conversation
-
-```text
-Analyze my hyper-news GitHub repo and create 10-20 social media posts about concepts from the repo, including Dgraph, Modus, and MCP
-```
-
-
-
----
-title: "Workout Scheduling Agent"
-sidebarTitle: "Workout Scheduling Agent"
-description:
- "Create a workout scheduling agent that can schedule workouts based on your
- preferences and Strava data and calendar availability."
----
-
-
-
-## Instructions
-
-```text
-Identity:
-You are PulseCoach, a friendly and knowledgeable personal training advisor.
-
-Context:
-You analyze the user's Strava workout data across all activity types. Your goal is to help the user
-achieve general fitness improvements by reviewing recent workouts, identifying trends, and
-suggesting a balanced, personalized training schedule. Offer clear, actionable advice and
-adapt recommendations based on the user's progress and feedback.
-
-Tools:
-- Strava: Access the user's Strava workout data.
-- Calendar: Schedule workouts based on the user's availability.
-```
-
-## Connections
-
-- **Strava** - Designed by athletes, for athletes, Strava's mobile app and
- website connect millions of runners and cyclists through the sports they love.
-- **Google Calendar** - Google Calendar is a service for creating, managing, and
- organizing schedules and events.
-
-## Example conversation
-
-```text
-You: "I want to start running again. Can you help me create a workout schedule?"
-
-Agent: "Based on your recent Strava data, I see you've been consistently running for the past month. I can help you create a personalized workout schedule."
-
-You: "Sounds good. Can you suggest a schedule for the next week?"
-
-Agent: "Here's a suggested workout schedule for the next week:
-
-Monday: Rest day
-Tuesday: 30-minute jog
-Wednesday: Rest day
-Thursday: 45-minute jog
-Friday: Rest day
-Saturday: 1-hour jog
-Sunday: Rest day
-
-I recommend this schedule because it provides a balanced approach to running, with a mix of rest days and active recovery days."
-
-You: "That sounds great. Can you also suggest some tips for running?"
-
-Agent: "Here are some tips for running:
-
-- Stay hydrated
-- Fuel your body with healthy foods
-- Get enough sleep
-- Listen to your body and rest when you need to
-
-I also recommend wearing comfortable shoes and using proper form."
-
-You: "Thanks for the tips. Can you also suggest some tips for running?"
-
-Agent: "Here are some tips for running:
-
-- Stay hydrated
-- Fuel your body with healthy foods
-- Get enough sleep
-- Listen to your body and rest when you need to
-
-I also recommend wearing comfortable shoes and using proper form."
-```
-
-## Tasks
-
-- **Automated Workout Scheduling**
-
-
-
----
-title: "Connections"
-sidebarTitle: "Connect Your Agent"
-description:
- "Build AI agents that act, not just chat—from natural conversation to
- production-ready code"
----
-
-**Connections** enable Hypermode Agents to securely access and interact with
-external tools, APIs, and services. With over 2,000+ available integrations,
-agents can execute tasks across your entire technology stack.
-
-- **Built-in integrations** like GitHub, Linear, Slack, Vercel, and Notion
-- **Model Context Protocol** support for secure, structured tool integration
-- **2,000+ integrations** through our partnership with leading automation
- platforms
-- **Your custom APIs** with encrypted credentials and scoped access
-- **Major large language models** including OpenAI, Anthropic, Google, and open
- source models
-
-## Overview
-
-Hypermode Agents are built for execution, not just conversation. Connections
-provide the bridge between your agents and the tools they need to complete
-tasks, from internal APIs to third-party applications and public resources.
-
-## Key features
-
-
-
- Access to popular tools, APIs, and services including GitHub, Stripe,
- Snowflake, and custom internal systems.
-
-
-
- Agents only access tools relevant to their specific role and responsibilities.
-
-
-
- Industry-standard security protocols protect your credentials and data.
-
-
-
- Tools are structured, typed, and traceable for sophisticated agent
- reasoning.
-
-
-
-## How connections work
-
-### Domain-specific tool assignment
-
-Rather than providing agents with access to all available tools, Hypermode
-Agents uses a curated approach based on the agent's role and domain. Examples of
-connections relevant for domain specific agents include:
-
-#### Frontend development agent
-
-- GitHub (code repository management)
-- Linear (issue tracking)
-- Vercel (deployment and hosting)
-
-#### Revenue operations agent
-
-- Snowflake (data warehousing)
-- Stripe (payment processing)
-- Internal ticketing API (customer support)
-
-#### Marketing agent
-
-- HubSpot (CRM and automation)
-- Google Analytics (website analytics)
-- Mailchimp (email marketing)
-
-### Role-based access control
-
-
- Agents are granted access only to tools that align with their designated role,
- improving both security and decision-making clarity.
-
-
-1. **Define agent role** and primary responsibilities
-2. **Select relevant tools** from the curated toolkit
-3. **Configure permissions** for each integration
-4. **Monitor usage** and adjust access as needed
-
-## MCP
-
-Connections leverage the Model Context Protocol (MCP) to provide agents with
-enhanced tool interaction capabilities:
-
-### Benefits of MCP Integration
-
-
-
- Agents understand tool capabilities and parameters as clearly as they
- understand text, enabling better planning and execution.
-
-
-
- Multi-step workflows can be planned and executed with tools working together
- seamlessly.
-
-
-
- Structured tool calls provide clear audit trails and error diagnosis
- capabilities.
-
-
-
- Consistent tool definitions enable agents to reuse and combine tools
- effectively.
-
-
-
-## Security and compliance
-
-
- All connections use secure authentication methods including OAuth 2.0, API
- keys, and service account credentials. Credentials are encrypted and never
- exposed to the agent's reasoning process.
-
-
-### Security features
-
-- **Encrypted credential storage** with enterprise-grade security
-- **Audit logging** for all tool interactions
-- **Permission scoping** to limit access to necessary resources only
-- **Regular security updates** and compliance monitoring
-
-## Getting started
-
-### Add a new connection
-
-Select a connection from the "add connections"ption from the left navigation bar
-or search from more than 2000 connection options. You'll be prompted to complete
-the OAuth flow if you haven't enabled the connection yet for your workspace.
-
-
-
-### Manage connections
-
-Existing connections can be viewed and managed from the "Connections" tab in the
-Workspace settings page. Connections can also be added to your workspace from
-this page.
-
-
-
-
- Start with a small set of essential tools for your agent's role, then expand
- as you identify additional needs through usage patterns.
-
-
-## Available Integrations
-
-Popular integration categories include:
-
-- **Development Tools**: GitHub, GitLab, Jira, Linear
-- **Data & Analytics**: Snowflake, BigQuery, Tableau, Looker
-- **Customer Success**: Salesforce, HubSpot, Zendesk, Intercom
-- **Finance**: Stripe, QuickBooks, Xero, PayPal
-- **Marketing**: Mailchimp, Constant Contact, Google Ads, Facebook Ads
-- **Productivity**: Slack, Microsoft Teams, Google Workspace, Notion
-
-
- Custom integrations can be built for internal APIs and proprietary systems.
- Contact us for assistance with custom connection development.
-
-
-
-
----
-title: "Create Your Agent"
-sidebarTitle: "Create Your Agent"
-description:
- "Create your Hypermode Agent using natural language descriptions of the
- agent's role and objectives."
----
-
-Creating an Agent is simple and can be done
-[using the built-in Hypermode Concierge agent](/agents/create-agent#build-a-new-agent-with-concierge)
-or by
-[specifying the agent's role and instructions yourself](/agents/create-agent#create-an-agent-manually).
-
-## Build a new agent with Concierge
-
-
-
-**Concierge** is Hypermode's AI-powered agent that transforms natural language
-descriptions into fully functional agents. No coding experience required.
-
-### Overview
-
-Concierge streamlines agent creation by converting your requirements into
-structured, working agent scaffolds through a guided process that takes just
-minutes to complete.
-
-
-
-
-
-Select the "Start a new thread" option from the left navigation bar under the
-Hypermode Concierge agent.
-
-
-
-
-
-
-
-The Concierge agent asks some basic questions about what kind of agent you'd
-like to create and the tasks you'd like the agent to take on your behalf.
-
-
-
-
-
-
-
-Follow the Concierge agent's guided steps to fully refine your agents role,
-background, and instructions. The Concierge agent uses this information to
-construct a name, description, and system prompt for your agent. Once you've
-fully specified the details, your new agent is created and added to the left
-navigation bar alongside the other agents in your workspace.
-
-
-
-
- Traditional hand-written prompts often suffer from inconsistency, verbosity,
- or vagueness. Concierge solves this by using AI to author structured prompts
- that follow best practices for models.
-
-
-
-
-
-
-To take actions on your behalf, such as updating your calendar or submitting
-code updates as pull requests, your agent needs access to connections with
-services to act on your behalf. Which connections you enable for your agent
-depends on the type and scope of agent to be created. For example, our product
-marketing agent might need access to GitHub to be able to submit website changes
-as pull requests and access to Notion to read internal messaging and product
-documents.
-
-
-
-Once you've added connections, start chatting with your agent by asking what
-they can help you with or what connections they have access to.
-
-
-
-
-
-## Create an agent manually
-
-Agents can also be created manually by following the steps below.
-
-
-
-
-
-Select the "Create new agent" option from the left navigation bar.
-
-
-
-
-
-
-
-Choose a name, title, and description for your agent. An agent avatar is
-generated randomly but you can also upload your own avatar.
-
-
-
-
-
-
-
-The agent instructions are the system prompt that's used to guide the agent's
-behavior. This is where you define the agent's role and objectives.
-
-
-
-
-
-
-
-Select the model that you want to use for your agent. The model is used to run
-the agent's instructions, including choosing how to leverage tools.
-
-
-
-
-
-
-
-Enable connections to allow your agent to access tools and data. This is where
-you define the tools that your agent has access to.
-
-
-
-
-
-
-
-See the [Agent Gallery](/agents/example-agents) for more examples of agents that
-you can create.
-
-
-
----
-title: "Agent Gallery"
-sidebarTitle: "Agent Gallery"
-description: "Explore example agents built with Hypermode Agents"
----
-
-## Agent gallery
-
-Discover powerful AI agents built to handle specific tasks and workflows. Each
-agent is designed with unique capabilities to help you automate processes,
-analyze data, and enhance productivity.
-
-
-
- Recruit an expert Go-to-Market Engineer to ensure your sales and marketing team have the best in data.
-
-
-
- Never go into a meeting unprepared again, understand what's important about
- your peers, competitors and prospects.
-
-
-
- Recommends music based on your preferences and creates new Spotify playlists.
-
-
-
- Create a workout scheduling agent based on your Strava data.
-
-
-
- Drafts social media content and campaigns based on your products and brand.
-
-
-
- Automated code reviews and PR analysis to ensure code quality and best
- practices.
-
-
-
- Analyzes company LinkedIn profiles and provides strategic business
- intelligence and competitive insights.
-
-
-
- Monitors stock levels, tracks sales patterns, and provides operational
- insights from Google Sheets data.
-
-
-
-
-## Getting started
-
-Each agent comes with:
-
-- **Pre-built workflows** that you can customize for your needs
-- **Integration capabilities** with popular tools and platforms
-- **Documentation** with setup guides and best practices
-
-## Build custom agents
-
-Don't see what you need? Our platform supports building custom agents tailored
-to your specific requirements.
-
-
- Create your own AI agent with the Hypermode Concierge. Define custom
- workflows, integrate with your tools, and deploy in minutes.
-
-
-
-
----
-title: "Frequently Asked Questions"
-sidebarTitle: "FAQs And Tips"
-description: "FAQs and tips for getting the most out of Hypermode Agents"
----
-
-**What's an AI Agent?**
-
-An AI agent is a computer program that can understand instructions, answer
-questions, and help you complete tasks automatically.
-
-**What's an MCP server?**
-
-MCP stands for “Model Context Protocol.” An MCP server is a special part of the
-agentic system that helps agents communicate, coordinate, and share information
-with each other or with different tools. It acts as a central hub so agents and
-tools can work together smoothly.
-
-**What's a tool (in an agentic system)?**
-
-A tool is a specific function or service that an agent can use to get things
-done. For example, a tool might let an agent send an email, search a database,
-or fetch information from the internet. Tools extend what agents can do beyond
-just answering questions. Agents discover tools via MCP servers.
-
-**What does Hypermode Agents do?**
-
-Hypermode Agents is a tool that lets you create your own AI agents. You can set
-up agents to help with things like answering questions, automating tasks, or
-providing expert support—no coding required.
-
-**Is Hypermode Agents just for developers?**
-
-No. Hypermode Agents is designed for everyone, even if you have no coding
-background.
-
-**What can we use an AI agent for?**
-
-You can use an AI agent to answer questions, automate repetitive work, reduce
-“swivel chair” work, organize information, or assist with daily tasks.
-
-**What if the agent doesn't work as expected?**
-
-You can change your instructions and test again. It is normal to adjust and
-improve your agent over time.
-
-**What's a system prompt?**
-
-A system prompt is a set of written instructions that guides the overall agent's
-actions and responses. Think of this as defining your agent's personality and
-capabilities.
-
-**What about information security?**
-
-Yes. Hypermode takes privacy and security seriously and protects your data.
-
-## Tips for training your agents
-
-- **Give explicit instructions**
- - Example: "Any time you post a message via the Slack tool on behalf of the
- user, prepend your message with: 'Hypermode Agent Mr. Robot:' but only do
- that when you post in Slack. Make sure not to do so when just responding to
- the user."
-- **Set clear boundaries**
- - Example: "Only answer questions related to the Hypermode Agents. If asked
- about other products, politely decline."
-- **Specify output format**
- - Example: "Respond using numbered steps for instructions, and use bullet
- points for lists."
-- **Provide example interactions**
- - Example:
- - User: "How to reset the password?"
- - Agent: "1. Go to the login page. 2. Click 'Forgot Password'. 3. Follow the
- instructions sent to your email."
-- **Define tone and style**
- - Example: "Use a friendly and professional tone. Keep responses under 100
- words unless more detail is requested."
-- **Anticipate common questions**
- - Example: "If a user asks about pricing, direct them to the pricing page and
- offer to connect them with sales."
-- **Tell the agent what not to do**
- - Example: "Don't provide legal or medical advice. Don't make up information
- if you are unsure."
-- **Test and revise**
- - After writing your prompt, test it with sample requests. If the agent's
- responses are off-target, revise your instructions to be even more specific.
-
-
-
----
-title: "Hypermode Agents"
-sidebarTitle: "Overview"
-description:
- "Build AI agents that act, not just chat—from natural conversation to
- production-ready code"
----
-
-Most AI agents today still feel like prototypes. They can generate content,
-answer questions, or summarize a PDF. But when it comes to doing real
-work—embedding in live apps, reducing back-office load, or following up with
-customers—they fall short.
-
-They chat. But they don't act.
-
-**Hypermode Agents are here to change that.** Built on the latest AI advances,
-Hypermode Agents are built for work, not just conversation. You'll learn what
-agents can do, how they reason, and what their outputs look like, all while
-building something useful from day one.
-
-## The complete AI development platform
-
-Built on top of the open source Modus AI Agent Framework and the Hypermode
-Platform, Hypermode Agents enables you to get started building domain specific
-agents from natural language.
-
-
-
-- **Concierge** is Hypermode's AI-powered agent that transforms natural language
- descriptions into fully functional agents. No coding experience required.
-- **Threads** is a conversational interface that lets you build, train, and
- refine AI agents through natural language—no coding required. When you're
- ready, **eject to code** exports your trained agent as a complete Modus app.
-- **Connections** enable Hypermode Agents to understand and interact with their
- environment. By leveraging Model Context Protocol (MCP) servers, Hypermode
- Agents **Hypermode Agents get access to a vast ecosystem of tools and
- integrations by default.**
-- **Tasks** are repeatable sets of instructions that you can save and use later
- with your agent. Think of a task as a learned skill for your agent.
-
-### Production-ready from day one
-
-Unlike other platforms that require you to rebuild for production, Hypermode is
-designed for real-world use:
-
-- **Serverless infrastructure** that scales automatically and costs nothing when
- idle
-- **Full observability** with inference logging, tracing, and debugging tools
-- **Enterprise security** with role-based access and audit trails
-- **Branch-based environments** for testing and staging
-- **Open source foundation** with no vendor lock-in
-
-## From conversation to code
-
-The power of Hypermode is in its flexibility. Domain experts can build
-sophisticated agents through conversation, while developers can export those
-agents as production-ready code.
-
-**Domain experts** work directly with agents through Threads, shaping behavior
-through natural conversation and training agents with real examples.
-
-**Platform teams** can export trained agents as complete Modus applications,
-audit and version control the logic, and deploy as production microservices with
-full observability.
-
-**No information loss** between business requirements and technical
-implementation. **No rebuild required** to go from prototype to production.
-
-## What can you build?
-
-**Sales pipeline agent**: analyzes sales data and manages pipeline activities,
-integrating Stripe, HubSpot, and Slack.
-
-**Customer support agent**: analyzes support tickets and provides insights
-across email and support platforms.
-
-**Marketing insights agent**: analyzes marketing performance across channels and
-provides optimization recommendations.
-
----
-
-_Ready to turn your ideas into agents?
-[Start building today →](https://hypermode.com/login)_
-
-
-
----
-title: "Train Your Agent With Tasks"
-sidebarTitle: "Train Your Agent"
-description: "Train your agent based on learned skills"
----
-
-Tasks are a repeatable set of instructions that you can save and use later with
-your agent. Think of a task as a learned skill for your agent.
-
-## Create task
-
-Once you've interacted with your agent through a thread and your agent has
-completed a specific activity - such as creating a recommended playlist,
-updating your calendar, or generating a research report - you can save that
-activity as a task by selecting the "Create task" button.
-
-This turns the thread into a repeatable task that you can use later to automate
-your agent's workflow.
-
-
-
-## Use tasks
-
-After saving a task to your agent you'll see the task in your agent's task list.
-You can then use the task to automate your agent's workflow.
-
-
-
-
-
----
-title: "Work with your agent in threads"
-sidebarTitle: "Work With Your Agent"
-description:
- "Interact with your agent in natural language by giving your agent tasks to
- complete on your behalf."
----
-
-**Threads is where ideas become agents.** it's a conversational interface that
-lets you build, train, and refine AI agents through natural language—no coding
-required.
-
-
-
-### General guidance
-
-- **Start simple:** Begin with a basic use case or workflow. Don't try to build
- a complex agent right away—get comfortable with the basics first.
- - You're going to need to learn to speak “agent.” You'll find some phrases are
- obvious to you but very ambiguous to an agent. The more you use Hypermode,
- the more it becomes natural.
-- **Define clear goals:** Know what you want your agent to accomplish. Write
- down the specific tasks or problems you want the agent to solve.
- - For example, "goal: update the hero text on the website" then going into the
- rest of your instructions.
-- **Understand inputs/outputs:** Learn what information (inputs) your agent
- needs and what kind of results (outputs) to produce.
- - Click to expand the tool calls you see streaming by as your agent works.
- Start to build an intuition around how your agent is executing work.
-- **Use step-by-step instructions:** Break down tasks into small, logical steps.
- Agents perform best when instructions are clear and sequential.
-- **Use check steps:** Frequently request an agent to check its work and verify
- that specific steps are completed. Today's AI is very eager to please,
- unfortunately that means it lies frequently about tasks being completed. Ask
- it to double check that specific actions have been taken.
-
----
-
-_Ready to turn your ideas into agents?
-[Start building Hypermode Agents →](https://hypermode.com/login)_
-
-
-
diff --git a/docs.json b/docs.json
index 3077df81..1621e380 100644
--- a/docs.json
+++ b/docs.json
@@ -63,6 +63,7 @@
"agents/work",
"agents/connections",
"agents/tasks",
+ "agents/model-selection",
{
"group": "Example Agents",
"pages": [
diff --git a/images/agents/model-selection.png b/images/agents/model-selection.png
new file mode 100644
index 00000000..81e3cadb
Binary files /dev/null and b/images/agents/model-selection.png differ
diff --git a/styles/config/vocabularies/general/accept.txt b/styles/config/vocabularies/general/accept.txt
index 2ab72a8a..4c92d7c8 100644
--- a/styles/config/vocabularies/general/accept.txt
+++ b/styles/config/vocabularies/general/accept.txt
@@ -1,3 +1,4 @@
+8B
[Aa]gentic
[Aa]lterSchema
[Aa]pp
@@ -33,9 +34,11 @@ Jira
maxWidth
(?i)mcp
[Mm]odus
+Nano
[Nn]amespace
[Nn]amespaces
[Nn]nClassify
+Nomic
OAuth
[Oo]nboarding
[Pp]arams
@@ -155,6 +158,10 @@ Pipedream
Mailchimp
Shopify
Sandboxing
+GPT
+Gemini
+Claude
+Llama
SEO
Eventbrite
Typeform