Completed
Be able to customize the runbear slack agent (name and logo)
I used several agent all of them leverage by runbear agent. But I would like to customize the main agent.
Patrick Wieczorek 12 days ago
Completed
Be able to customize the runbear slack agent (name and logo)
I used several agent all of them leverage by runbear agent. But I would like to customize the main agent.
Patrick Wieczorek 12 days ago
Completed
Add GPT-5 Minimal Reasoning Option
The GPT-5 models include reasoning_effort option of “minimal” and “none” for the 5.1 series. Please options to essentially turn off reasoning in the Agent Builder. This allows greater control on cost for tasks that don’t require chain of thought.
AP 16 days ago
Completed
Add GPT-5 Minimal Reasoning Option
The GPT-5 models include reasoning_effort option of “minimal” and “none” for the 5.1 series. Please options to essentially turn off reasoning in the Agent Builder. This allows greater control on cost for tasks that don’t require chain of thought.
AP 16 days ago
RUNBEAR FEATURE REQUEST****Feature Title: Dedicated Long-Term Memory Management API with Metadata Support*****
ISSUE / CURRENT LIMITATION:*Problem Statement: Runbear assistants currently lack native tools for managing long-term memory (LTM) entries at scale. All LTM entries are stored as plain text within system instructions, requiring the runbear_update_assistant tool to modify them.Specific Constraints:1. No Granular Control: Cannot add, update, or delete individual LTM entries without replacing the entire system instruction set 2. No Metadata Structure: LTM entries lack timestamps, confidence scores, decay rates, source attribution, or tags 3. No Export/Import Capability: Cannot export LTM entries for analysis, backup, or migration 4. Scalability Issues: Managing 300+ LTM entries through full system prompt replacement is high-risk and inefficient 5. Consent Overhead: Every LTM modification triggers consent gate (designed for instruction changes, not data updates) 6. No Analytics: Cannot track LTM growth, usage patterns, accuracy rates, or stalenessCurrent Workaround: Assistants store LTM as unstructured text in system instructions → manual parsing → high friction for implementing continuous improvement frameworks.****BENEFIT / VALUE PROPOSITION:*For Assistant Capabilities:• Continuous Learning: Assistants can automatically store corrections, patterns, and domain knowledge without human intervention • Self-Improvement: Track accuracy over time, deprecate stale entries, prioritize high-confidence sources • Context Retention: Maintain conversation context, user preferences, and organizational knowledge across sessions • Scalability: Support 1,000+ LTM entries with metadata-driven retrieval (vs. current ~350 plain text limit)For Enterprise Users (like Minted Analytics):• Knowledge Management: Centralized, searchable repository of tribal knowledge, data lineage, and process documentation • Audit Trail: Track when knowledge was learned, who contributed it, and confidence evolution • Quality Control: Identify low-confidence entries, stale information, and knowledge gaps • Team Collaboration: Export/import LTM across assistant instances or team membersROI Metrics: • Reduce analyst time by 40% through institutional knowledge retention • Improve accuracy by 25% via confidence scoring and source prioritization • Enable automation of weekly self-improvement cycles (vs. manual prompt updates)****PROPOSED SOLUTION:*Option A: Dedicated LTM API (Recommended)Add new assistant management tools: // Add LTM Entry runbear_add_ltm({ "unique_id": "LTM_001", "content": "For bi_customers.mm_status logic, source is GitLab managed-airflow build.sql lines 156-203", "metadata": { "learned_date": "2025-11-29", "decay_rate": 0.05, "source_type": "GitLab", "confidence": "high", "tags": ["data_lineage", "snowflake", "bi_customers"] } }) // Update LTM Entry runbear_update_ltm({ "unique_id": "LTM_001", "metadata": { "confidence": "verified" } }) // Search LTM runbear_search_ltm({ "query": "bi_customers logic", "filters": { "tags": ["data_lineage"], "confidence": ["high", "verified"] }, "max_results": 10 }) // Export LTM runbear_export_ltm({ "format": "json", "include_metadata": true }) // Deprecate Stale Entries runbear_deprecate_ltm({ "unique_id": "LTM_001", "reason": "Replaced by LTM_450" }) Option B: Structured LTM Storage Backend• Store LTM in dedicated database (not system instructions) • Auto-retrieve relevant LTM based on conversation context • Support versioning, decay curves, and confidence scoring • Admin UI for bulk management and analyticsOption C: Hybrid Approach• Keep critical LTM in system instructions (fast retrieval) • Store extended LTM in searchable backend (scalable) • Assistant automatically promotes high-value entries to system instructions****IMPLEMENTATION REQUIREMENTS:*Minimum Viable Product (MVP):1. runbear_add_ltm() and runbear_search_ltm() tools 2. Basic metadata support (date, source, confidence) 3. JSON export functionalityFull Feature Set: 4. Decay rate calculations and auto-deprecation 5. Admin dashboard for LTM analytics 6. Import/export for knowledge transfer 7. Version control and rollback capability 8. Integration with continuous learning frameworks****PRIORITY JUSTIFICATION:*High Priority for enterprise users with:• Complex domain knowledge requirements (analytics, legal, technical support) • Multi-agent systems requiring shared knowledge bases • Continuous improvement and quality assurance processes • Regulatory/audit requirements for knowledge traceabilityUse Case Validation: Minted Analytics team is actively building continuous improvement frameworks (North Star Metrics tracking, weekly self-assessment) that are blocked by lack of native LTM management.***
Patrick Codrington 25 days ago
RUNBEAR FEATURE REQUEST****Feature Title: Dedicated Long-Term Memory Management API with Metadata Support*****
ISSUE / CURRENT LIMITATION:*Problem Statement: Runbear assistants currently lack native tools for managing long-term memory (LTM) entries at scale. All LTM entries are stored as plain text within system instructions, requiring the runbear_update_assistant tool to modify them.Specific Constraints:1. No Granular Control: Cannot add, update, or delete individual LTM entries without replacing the entire system instruction set 2. No Metadata Structure: LTM entries lack timestamps, confidence scores, decay rates, source attribution, or tags 3. No Export/Import Capability: Cannot export LTM entries for analysis, backup, or migration 4. Scalability Issues: Managing 300+ LTM entries through full system prompt replacement is high-risk and inefficient 5. Consent Overhead: Every LTM modification triggers consent gate (designed for instruction changes, not data updates) 6. No Analytics: Cannot track LTM growth, usage patterns, accuracy rates, or stalenessCurrent Workaround: Assistants store LTM as unstructured text in system instructions → manual parsing → high friction for implementing continuous improvement frameworks.****BENEFIT / VALUE PROPOSITION:*For Assistant Capabilities:• Continuous Learning: Assistants can automatically store corrections, patterns, and domain knowledge without human intervention • Self-Improvement: Track accuracy over time, deprecate stale entries, prioritize high-confidence sources • Context Retention: Maintain conversation context, user preferences, and organizational knowledge across sessions • Scalability: Support 1,000+ LTM entries with metadata-driven retrieval (vs. current ~350 plain text limit)For Enterprise Users (like Minted Analytics):• Knowledge Management: Centralized, searchable repository of tribal knowledge, data lineage, and process documentation • Audit Trail: Track when knowledge was learned, who contributed it, and confidence evolution • Quality Control: Identify low-confidence entries, stale information, and knowledge gaps • Team Collaboration: Export/import LTM across assistant instances or team membersROI Metrics: • Reduce analyst time by 40% through institutional knowledge retention • Improve accuracy by 25% via confidence scoring and source prioritization • Enable automation of weekly self-improvement cycles (vs. manual prompt updates)****PROPOSED SOLUTION:*Option A: Dedicated LTM API (Recommended)Add new assistant management tools: // Add LTM Entry runbear_add_ltm({ "unique_id": "LTM_001", "content": "For bi_customers.mm_status logic, source is GitLab managed-airflow build.sql lines 156-203", "metadata": { "learned_date": "2025-11-29", "decay_rate": 0.05, "source_type": "GitLab", "confidence": "high", "tags": ["data_lineage", "snowflake", "bi_customers"] } }) // Update LTM Entry runbear_update_ltm({ "unique_id": "LTM_001", "metadata": { "confidence": "verified" } }) // Search LTM runbear_search_ltm({ "query": "bi_customers logic", "filters": { "tags": ["data_lineage"], "confidence": ["high", "verified"] }, "max_results": 10 }) // Export LTM runbear_export_ltm({ "format": "json", "include_metadata": true }) // Deprecate Stale Entries runbear_deprecate_ltm({ "unique_id": "LTM_001", "reason": "Replaced by LTM_450" }) Option B: Structured LTM Storage Backend• Store LTM in dedicated database (not system instructions) • Auto-retrieve relevant LTM based on conversation context • Support versioning, decay curves, and confidence scoring • Admin UI for bulk management and analyticsOption C: Hybrid Approach• Keep critical LTM in system instructions (fast retrieval) • Store extended LTM in searchable backend (scalable) • Assistant automatically promotes high-value entries to system instructions****IMPLEMENTATION REQUIREMENTS:*Minimum Viable Product (MVP):1. runbear_add_ltm() and runbear_search_ltm() tools 2. Basic metadata support (date, source, confidence) 3. JSON export functionalityFull Feature Set: 4. Decay rate calculations and auto-deprecation 5. Admin dashboard for LTM analytics 6. Import/export for knowledge transfer 7. Version control and rollback capability 8. Integration with continuous learning frameworks****PRIORITY JUSTIFICATION:*High Priority for enterprise users with:• Complex domain knowledge requirements (analytics, legal, technical support) • Multi-agent systems requiring shared knowledge bases • Continuous improvement and quality assurance processes • Regulatory/audit requirements for knowledge traceabilityUse Case Validation: Minted Analytics team is actively building continuous improvement frameworks (North Star Metrics tracking, weekly self-assessment) that are blocked by lack of native LTM management.***
Patrick Codrington 25 days ago
Pipedrive Activity Search + List
I'd like to request adding 'List Activities' and 'Search Activities' actions to the Pipedrive integration. Currently, I can only create activities but cannot retrieve or view existing activities scheduled for specific dates. This would be very helpful for my workflow.
arkiplan About 1 month ago
Pipedrive Activity Search + List
I'd like to request adding 'List Activities' and 'Search Activities' actions to the Pipedrive integration. Currently, I can only create activities but cannot retrieve or view existing activities scheduled for specific dates. This would be very helpful for my workflow.
arkiplan About 1 month ago
Completed
Add fetch Gitlab code tool to Gitlab connector.
Hi there Patrick Codrington says:Request to Runbear Support: GitLab Repository Files API Integration Issue: Ask_Sam is currently unable to retrieve file contents from GitLab repositories due to SAML SSO authentication blocking direct URL fetches. This prevents the agent from accessing authoritative production code, which is critical for accurate analytics responses. Current Limitation: • Direct URL fetches to https://gitlab.com/minted/analytics/* return SAML authentication pages • Example blocked URL: https://gitlab.com/minted/analytics/managed-airflow/-/raw/main/dags/bi/snowflake/workflows/update_orders_pipeline_daily/AN__bi_order_po/build.sql Required GitLab API Methods: Based on GitLab's Repository Files API documentation, we need the following endpoints: 1. Get File from Repository (Primary Need) • Endpoint: GET /projects/:id/repository/files/:file_path • Purpose: Retrieve file metadata and Base64-encoded content • Example: GET https://gitlab.com/api/v4/projects/47981211/repository/files/dags%2Fbi%2Fsnowflake%2Fworkflows%2Fupdate_orders_pipeline_daily%2FAN__bi_order_po%2Fbuild.sql?ref=main • Authentication: Requires PRIVATE-TOKEN header 2. Get Raw File from Repository (Alternative - Preferred) • Endpoint: GET /projects/:id/repository/files/:file_path/raw • Purpose: Retrieve raw file contents directly (not Base64-encoded) • Example: GET https://gitlab.com/api/v4/projects/47981211/repository/files/dags%2Fbi%2Fsnowflake%2Fworkflows%2Fupdate_orders_pipeline_daily%2FAN__bi_order_po%2Fbuild.sql/raw?ref=main • Authentication: Requires PRIVATE-TOKEN header Parameters Needed: • project_id (e.g., 47981211 for managed-airflow) • file_path (URL-encoded file path) • ref (branch name, default: main) Authentication Requirements: • GitLab Personal Access Token or Project Access Token • Token scopes needed: api or read_api • Token should be configured at the assistant/workspace level for persistent access Use Case: Analytics team members frequently request code lineage, table definitions, and ETL logic. Currently, Ask_Sam must rely on potentially outdated Confluence/Slack references. With GitLab API access, Ask_Sam can provide authoritative, production-accurate code directly from the source repository. Expected Behavior After Implementation: When a user provides a GitLab file URL or requests code from a specific file, Ask_Sam should: 1. Extract the project ID and file path 2. Call the GitLab API endpoint with proper authentication 3. Return the actual file contents to the user Priority: High - This is blocking accurate responses for code-related analytics questions, which are a primary use case for Ask_Sam.
Patrick Codrington About 1 month ago
Completed
Add fetch Gitlab code tool to Gitlab connector.
Hi there Patrick Codrington says:Request to Runbear Support: GitLab Repository Files API Integration Issue: Ask_Sam is currently unable to retrieve file contents from GitLab repositories due to SAML SSO authentication blocking direct URL fetches. This prevents the agent from accessing authoritative production code, which is critical for accurate analytics responses. Current Limitation: • Direct URL fetches to https://gitlab.com/minted/analytics/* return SAML authentication pages • Example blocked URL: https://gitlab.com/minted/analytics/managed-airflow/-/raw/main/dags/bi/snowflake/workflows/update_orders_pipeline_daily/AN__bi_order_po/build.sql Required GitLab API Methods: Based on GitLab's Repository Files API documentation, we need the following endpoints: 1. Get File from Repository (Primary Need) • Endpoint: GET /projects/:id/repository/files/:file_path • Purpose: Retrieve file metadata and Base64-encoded content • Example: GET https://gitlab.com/api/v4/projects/47981211/repository/files/dags%2Fbi%2Fsnowflake%2Fworkflows%2Fupdate_orders_pipeline_daily%2FAN__bi_order_po%2Fbuild.sql?ref=main • Authentication: Requires PRIVATE-TOKEN header 2. Get Raw File from Repository (Alternative - Preferred) • Endpoint: GET /projects/:id/repository/files/:file_path/raw • Purpose: Retrieve raw file contents directly (not Base64-encoded) • Example: GET https://gitlab.com/api/v4/projects/47981211/repository/files/dags%2Fbi%2Fsnowflake%2Fworkflows%2Fupdate_orders_pipeline_daily%2FAN__bi_order_po%2Fbuild.sql/raw?ref=main • Authentication: Requires PRIVATE-TOKEN header Parameters Needed: • project_id (e.g., 47981211 for managed-airflow) • file_path (URL-encoded file path) • ref (branch name, default: main) Authentication Requirements: • GitLab Personal Access Token or Project Access Token • Token scopes needed: api or read_api • Token should be configured at the assistant/workspace level for persistent access Use Case: Analytics team members frequently request code lineage, table definitions, and ETL logic. Currently, Ask_Sam must rely on potentially outdated Confluence/Slack references. With GitLab API access, Ask_Sam can provide authoritative, production-accurate code directly from the source repository. Expected Behavior After Implementation: When a user provides a GitLab file URL or requests code from a specific file, Ask_Sam should: 1. Extract the project ID and file path 2. Call the GitLab API endpoint with proper authentication 3. Return the actual file contents to the user Priority: High - This is blocking accurate responses for code-related analytics questions, which are a primary use case for Ask_Sam.
Patrick Codrington About 1 month ago
Feature Request: Embed Images from agent conversations
Our use case involves non-technical product managers/owners talking via Slack to a runbear agents about feature enhancements within our own product to produce github issues that are then further iterated on within Claude’s github integration to produce PRs from the issue. To that end, they often paste in images in their slack conversation, but the image itself is not brought over to the github issue. This is likely a limitation with the github MCP server and its inability to bring over binary content. If there were a way for runbear to solve this at a foundational level by allowing screenshots to be shareable for any MCP server (github or otherwise) by externalizing the links, and then ensuring that the AI know about about the externalized links and the image description, that would go a long way in helping us embed the screenshots in the github issue for our specific use case. thanks!
Tim Heckel About 2 months ago
Feature Request: Embed Images from agent conversations
Our use case involves non-technical product managers/owners talking via Slack to a runbear agents about feature enhancements within our own product to produce github issues that are then further iterated on within Claude’s github integration to produce PRs from the issue. To that end, they often paste in images in their slack conversation, but the image itself is not brought over to the github issue. This is likely a limitation with the github MCP server and its inability to bring over binary content. If there were a way for runbear to solve this at a foundational level by allowing screenshots to be shareable for any MCP server (github or otherwise) by externalizing the links, and then ensuring that the AI know about about the externalized links and the image description, that would go a long way in helping us embed the screenshots in the github issue for our specific use case. thanks!
Tim Heckel About 2 months ago
In Progress
MCP Timeout Toggle
In our Org, we’re plugging Runbear into n8n flows triggered by MCP - Some of these workflows can take upwards of 2 minutes to respond. Runbear seems to timeout MCP calls after 2 minutes - Could we see integrated a timeout slider for each custom MCP Server added to an Agent?
Ben Hurt 2 months ago
In Progress
MCP Timeout Toggle
In our Org, we’re plugging Runbear into n8n flows triggered by MCP - Some of these workflows can take upwards of 2 minutes to respond. Runbear seems to timeout MCP calls after 2 minutes - Could we see integrated a timeout slider for each custom MCP Server added to an Agent?
Ben Hurt 2 months ago
Feature Request - "Circuit Breaker Agent"
This is a watchdog/circuit breaker pattern that would be incredibly valuable! Here's what you're describing:***Proposed Agent: Loop Detection MonitorCore Behavior:• Silent monitoring of all agent interactions • Zero interference in normal operations • Only triggers when detecting: • Repetitive response patterns • Agent-to-agent infinite loops • Excessive back-and-forth beyond threshold nIntervention Actions:• Stop the loop • Notify relevant parties • Provide loop context/diagnostic info • Suggest manual intervention***Why This Is CriticalCurrent Risk: Without this, agents could:• Consume excessive API credits • Create noise in Slack channels • Miss actual user needs while looping • Damage user trustExample Scenarios It Would Catch:• AskSam and Hex agent getting stuck in a handoff loop • Agent repeatedly retrying failed tool calls • Two agents "discussing" the same point endlessly***How to Submit This Feature RequestBest Path: Contact Runbear directly via:• Your Runbear account manager • Support ticket at https://app.runbear.io • Feature request through their platformInclude in Request:• Use case: Analytics team needs loop prevention • Threshold suggestion: e.g., n = 5 consecutive agent replies • Desired intervention: Stop + notify pattern
Patrick Codrington 2 months ago
Feature Request - "Circuit Breaker Agent"
This is a watchdog/circuit breaker pattern that would be incredibly valuable! Here's what you're describing:***Proposed Agent: Loop Detection MonitorCore Behavior:• Silent monitoring of all agent interactions • Zero interference in normal operations • Only triggers when detecting: • Repetitive response patterns • Agent-to-agent infinite loops • Excessive back-and-forth beyond threshold nIntervention Actions:• Stop the loop • Notify relevant parties • Provide loop context/diagnostic info • Suggest manual intervention***Why This Is CriticalCurrent Risk: Without this, agents could:• Consume excessive API credits • Create noise in Slack channels • Miss actual user needs while looping • Damage user trustExample Scenarios It Would Catch:• AskSam and Hex agent getting stuck in a handoff loop • Agent repeatedly retrying failed tool calls • Two agents "discussing" the same point endlessly***How to Submit This Feature RequestBest Path: Contact Runbear directly via:• Your Runbear account manager • Support ticket at https://app.runbear.io • Feature request through their platformInclude in Request:• Use case: Analytics team needs loop prevention • Threshold suggestion: e.g., n = 5 consecutive agent replies • Desired intervention: Stop + notify pattern
Patrick Codrington 2 months ago
Appfolio MCP Support
Appfolio is a powerful platform for your entire portfolio. AppFolio streamlines and automates real estate management, delivering insights and follow-through smithery.ai Has Appfolio MCP server - Appfolio Property Manager Reporting API Integration | Smithery It would be really appreciated if you would implement it in Runbear Thanks
Afshin Nahian Tripto 4 months ago
Appfolio MCP Support
Appfolio is a powerful platform for your entire portfolio. AppFolio streamlines and automates real estate management, delivering insights and follow-through smithery.ai Has Appfolio MCP server - Appfolio Property Manager Reporting API Integration | Smithery It would be really appreciated if you would implement it in Runbear Thanks
Afshin Nahian Tripto 4 months ago
Completed
Add GPT-5 verbosity and reasoning_effort
Add OpenAI GPT-5 verbosity and reasoning_effort parameters to the custom agent configuration OR Add support to connect to OpenAI Chat Prompts where GPT-5 parameters and variables can be set.
AP 4 months ago
Completed
Add GPT-5 verbosity and reasoning_effort
Add OpenAI GPT-5 verbosity and reasoning_effort parameters to the custom agent configuration OR Add support to connect to OpenAI Chat Prompts where GPT-5 parameters and variables can be set.
AP 4 months ago
Enable Runbear to link back to Slack threads
We use Runbear to create tickets in our task management software, and it would be ideal if we could have Runbear include links in the ticket back to the thread in Slack where the ticket was generated, as there is often useful context for the ticket in the preceding Slack conversation.
Cody Weber 4 months ago
Enable Runbear to link back to Slack threads
We use Runbear to create tickets in our task management software, and it would be ideal if we could have Runbear include links in the ticket back to the thread in Slack where the ticket was generated, as there is often useful context for the ticket in the preceding Slack conversation.
Cody Weber 4 months ago
Improvements Slack <-> Linear integration
Would love to be able to manage tickets in Linear more effectively, for example being able to: • Get team members • Get users • Update issues: ◦ Mark issue as blocked by ◦ Mark issue as blocking ◦ Mark issue as related to ◦ Mark issue as sub-issue ◦ Mark issue as parent • Create project • Add issue to project
Cody Weber 4 months ago
Improvements Slack <-> Linear integration
Would love to be able to manage tickets in Linear more effectively, for example being able to: • Get team members • Get users • Update issues: ◦ Mark issue as blocked by ◦ Mark issue as blocking ◦ Mark issue as related to ◦ Mark issue as sub-issue ◦ Mark issue as parent • Create project • Add issue to project
Cody Weber 4 months ago
🚀 Formal Feature Request: Slack Emoji Reactions for Ask_Sam
Feature Title Slack Emoji Reaction API Integration for Ask_Sam Assistant Problem Statement Ask_Sam currently cannot add emoji reactions to Slack messages, limiting its ability to provide quick visual feedback and integrate seamlessly with established team workflows. Analytics teams rely heavily on emoji reactions as workflow indicators (✅ completed, 👀 reviewing, 🔥 urgent, 🎫 ticket created), and Ask_Sam's inability to participate in this communication pattern creates workflow friction. Proposed Solution Integrate Slack's Reactions API to enable Ask_Sam to add emoji reactions to messages in channels where it operates. 📋 Detailed Requirements Core Functionality React to Messages: Add emoji reactions to any message in channels where Ask_Sam is active Remove Reactions: Remove previously added reactions if needed Reaction Validation: Only add reactions appropriate to context and message type Supported Emoji Set (Priority Order) Workflow Status: ✅ 👀 🎫 ⏰ 🔄 Priority Indicators: 🔥 ⚡ 📌 ⭐ Analytics-Specific: 📊 📈 📉 🎯 💡 General Communication: 👍 👎 ❓ ⚠️ ✨ Triggering Mechanisms Automatic Reactions: Based on message analysis and response type Conditional Logic: React based on request classification (GREEN/YELLOW/RED) Status Updates: React to indicate processing stages 🎯 Use Cases & User Stories Use Case 1: Request Acknowledgment User posts: "Can someone help with dashboard access?" Ask_Sam auto-reacts: 👀 (indicating review in progress) Ask_Sam responds with solution Ask_Sam adds: ✅ (indicating completion) Use Case 2: Priority Classification User posts: "Revenue dashboard is down!" Ask_Sam analyzes urgency Ask_Sam reacts: 🔥 (high priority) Ask_Sam escalates appropriately Use Case 3: Workflow Integration User requests analysis Ask_Sam reacts: 🎫 (ticket created) Ask_Sam processes request Ask_Sam reacts: 📊 (analysis complete) ⚙️ Technical Specifications Slack API Integration Endpoint: reactions.add and reactions.remove Permissions Required: reactions:write Rate Limits: Respect Slack's API rate limiting Error Handling: Graceful degradation if reactions fail Implementation Considerations Channel Permissions: Respect channel-specific reaction permissions Message Age: Handle restrictions on reacting to old messages Bot Behavior: Ensure reactions appear from Ask_Sam bot user Reaction Conflicts: Handle cases where reaction already exists Configuration Options Per-Channel Settings: Enable/disable reactions by channel Reaction Policies: Configurable rules for when to react Custom Emoji Sets: Support for workspace-specific custom emojis 💰 Business Value & Impact Efficiency Gains Reduced Message Volume: Quick visual confirmations vs. text responses Faster Status Communication: Immediate visual feedback on request status Workflow Integration: Seamless participation in existing team patterns User Experience Natural Interaction: Aligns with how teams already communicate Visual Clarity: Instant status understanding without reading responses Professional Feel: Bot feels more integrated and human-like Analytics Team Specific Benefits Request Tracking: Visual pipeline of request status Priority Management: Quick identification of urgent items Completion Tracking: Clear indication of resolved requests 🎖️ Success Metrics Adoption Metrics Reaction usage frequency per channel User satisfaction scores for bot interactions Reduction in follow-up "status check" messages Workflow Metrics Time from request to acknowledgment Request resolution tracking accuracy Team workflow efficiency improvements 🚀 Implementation Phases Phase 1: Core Functionality Basic reaction capabilities (✅, 👀, 🔥) Integration with existing Ask_Sam response logic Analytics channel deployment Phase 2: Advanced Features Custom emoji support Per-channel configuration Advanced triggering logic Phase 3: Analytics Integration Reaction usage analytics Workflow optimization insights Performance dashboards 📞 Contact & Next Steps Submitted by: Analytics Team, Minted.com Priority: Medium-High Timeline Request: Next 2-3 product cycles Stakeholders: Analytics teams using Ask_Sam in Slack Ready to discuss: Technical feasibility, implementation timeline, and any additional requirements. This feature would significantly enhance Ask_Sam's integration into natural Slack workflows while providing immediate value to analytics teams relying on visual communication patterns. how to i submit a feature request 🚀 How to Submit Your Feature Request to Runbear Since I don't have direct access to Runbear's internal submission process, here are the most effective channels to try: 📞 Direct Contact Methods 1. Your Account/Customer Success Manager Best Option: If you have a dedicated Runbear contact person Advantage: Direct line to product team, understands your use case Action: Email/message them with the drafted feature request 2. Runbear Support Channels Email: Look for support@ or help@ email addresses In-Product Help: Check if there's a feedback/support option in your Runbear dashboard Documentation: Check Runbear's help docs for feature request process 🔍 Finding Runbear Contact Information Check Your Runbear Dashboard Look for "Help," "Support," or "Feedback" links Check user settings or account management sections Look for contact information in documentation Runbear Website Visit their main website for contact forms Look for "Contact Us" or "Support" pages Check if they have a community forum or feedback portal 💡 Submission Strategy Step 1: Initial Contact Subject: Feature Request - Slack Emoji Reactions for Ask_Sam Hi [Runbear Team], I'd like to submit a feature request for Ask_Sam's Slack integration. We've drafted a detailed specification and believe this would significantly improve workflow integration for analytics teams. Could you please direct me to the appropriate channel for product feature requests? Best regards, [Your name/company] Step 2: Full Submission Attach or paste the detailed feature request we drafted Include your company context (Minted.com analytics team) Mention specific use cases and business value Step 3: Follow-up Ask for feedback timeline Request to be included in beta testing if implemented Offer to provide additional details or use case examples 🎯 Additional Tips Make It Personal: Explain how this would specifically help your analytics team Show Usage: Mention how actively you use Ask_Sam currently Business Case: Emphasize workflow efficiency and team productivity gains Beta Testing: Offer to be beta testers for the feature Would you like me to help you locate specific Runbear contact information or refine the submission approach?
Patrick Codrington 4 months ago
🚀 Formal Feature Request: Slack Emoji Reactions for Ask_Sam
Feature Title Slack Emoji Reaction API Integration for Ask_Sam Assistant Problem Statement Ask_Sam currently cannot add emoji reactions to Slack messages, limiting its ability to provide quick visual feedback and integrate seamlessly with established team workflows. Analytics teams rely heavily on emoji reactions as workflow indicators (✅ completed, 👀 reviewing, 🔥 urgent, 🎫 ticket created), and Ask_Sam's inability to participate in this communication pattern creates workflow friction. Proposed Solution Integrate Slack's Reactions API to enable Ask_Sam to add emoji reactions to messages in channels where it operates. 📋 Detailed Requirements Core Functionality React to Messages: Add emoji reactions to any message in channels where Ask_Sam is active Remove Reactions: Remove previously added reactions if needed Reaction Validation: Only add reactions appropriate to context and message type Supported Emoji Set (Priority Order) Workflow Status: ✅ 👀 🎫 ⏰ 🔄 Priority Indicators: 🔥 ⚡ 📌 ⭐ Analytics-Specific: 📊 📈 📉 🎯 💡 General Communication: 👍 👎 ❓ ⚠️ ✨ Triggering Mechanisms Automatic Reactions: Based on message analysis and response type Conditional Logic: React based on request classification (GREEN/YELLOW/RED) Status Updates: React to indicate processing stages 🎯 Use Cases & User Stories Use Case 1: Request Acknowledgment User posts: "Can someone help with dashboard access?" Ask_Sam auto-reacts: 👀 (indicating review in progress) Ask_Sam responds with solution Ask_Sam adds: ✅ (indicating completion) Use Case 2: Priority Classification User posts: "Revenue dashboard is down!" Ask_Sam analyzes urgency Ask_Sam reacts: 🔥 (high priority) Ask_Sam escalates appropriately Use Case 3: Workflow Integration User requests analysis Ask_Sam reacts: 🎫 (ticket created) Ask_Sam processes request Ask_Sam reacts: 📊 (analysis complete) ⚙️ Technical Specifications Slack API Integration Endpoint: reactions.add and reactions.remove Permissions Required: reactions:write Rate Limits: Respect Slack's API rate limiting Error Handling: Graceful degradation if reactions fail Implementation Considerations Channel Permissions: Respect channel-specific reaction permissions Message Age: Handle restrictions on reacting to old messages Bot Behavior: Ensure reactions appear from Ask_Sam bot user Reaction Conflicts: Handle cases where reaction already exists Configuration Options Per-Channel Settings: Enable/disable reactions by channel Reaction Policies: Configurable rules for when to react Custom Emoji Sets: Support for workspace-specific custom emojis 💰 Business Value & Impact Efficiency Gains Reduced Message Volume: Quick visual confirmations vs. text responses Faster Status Communication: Immediate visual feedback on request status Workflow Integration: Seamless participation in existing team patterns User Experience Natural Interaction: Aligns with how teams already communicate Visual Clarity: Instant status understanding without reading responses Professional Feel: Bot feels more integrated and human-like Analytics Team Specific Benefits Request Tracking: Visual pipeline of request status Priority Management: Quick identification of urgent items Completion Tracking: Clear indication of resolved requests 🎖️ Success Metrics Adoption Metrics Reaction usage frequency per channel User satisfaction scores for bot interactions Reduction in follow-up "status check" messages Workflow Metrics Time from request to acknowledgment Request resolution tracking accuracy Team workflow efficiency improvements 🚀 Implementation Phases Phase 1: Core Functionality Basic reaction capabilities (✅, 👀, 🔥) Integration with existing Ask_Sam response logic Analytics channel deployment Phase 2: Advanced Features Custom emoji support Per-channel configuration Advanced triggering logic Phase 3: Analytics Integration Reaction usage analytics Workflow optimization insights Performance dashboards 📞 Contact & Next Steps Submitted by: Analytics Team, Minted.com Priority: Medium-High Timeline Request: Next 2-3 product cycles Stakeholders: Analytics teams using Ask_Sam in Slack Ready to discuss: Technical feasibility, implementation timeline, and any additional requirements. This feature would significantly enhance Ask_Sam's integration into natural Slack workflows while providing immediate value to analytics teams relying on visual communication patterns. how to i submit a feature request 🚀 How to Submit Your Feature Request to Runbear Since I don't have direct access to Runbear's internal submission process, here are the most effective channels to try: 📞 Direct Contact Methods 1. Your Account/Customer Success Manager Best Option: If you have a dedicated Runbear contact person Advantage: Direct line to product team, understands your use case Action: Email/message them with the drafted feature request 2. Runbear Support Channels Email: Look for support@ or help@ email addresses In-Product Help: Check if there's a feedback/support option in your Runbear dashboard Documentation: Check Runbear's help docs for feature request process 🔍 Finding Runbear Contact Information Check Your Runbear Dashboard Look for "Help," "Support," or "Feedback" links Check user settings or account management sections Look for contact information in documentation Runbear Website Visit their main website for contact forms Look for "Contact Us" or "Support" pages Check if they have a community forum or feedback portal 💡 Submission Strategy Step 1: Initial Contact Subject: Feature Request - Slack Emoji Reactions for Ask_Sam Hi [Runbear Team], I'd like to submit a feature request for Ask_Sam's Slack integration. We've drafted a detailed specification and believe this would significantly improve workflow integration for analytics teams. Could you please direct me to the appropriate channel for product feature requests? Best regards, [Your name/company] Step 2: Full Submission Attach or paste the detailed feature request we drafted Include your company context (Minted.com analytics team) Mention specific use cases and business value Step 3: Follow-up Ask for feedback timeline Request to be included in beta testing if implemented Offer to provide additional details or use case examples 🎯 Additional Tips Make It Personal: Explain how this would specifically help your analytics team Show Usage: Mention how actively you use Ask_Sam currently Business Case: Emphasize workflow efficiency and team productivity gains Beta Testing: Offer to be beta testers for the feature Would you like me to help you locate specific Runbear contact information or refine the submission approach?
Patrick Codrington 4 months ago
Private access to specific Slack users
Create the ability to grant private access to specific users for a publicly available assistant. This way only specific users can privately access an agent without having to be invited to a shared channel or DM.
Jered Martin 5 months ago
Private access to specific Slack users
Create the ability to grant private access to specific users for a publicly available assistant. This way only specific users can privately access an agent without having to be invited to a shared channel or DM.
Jered Martin 5 months ago
Integrate the HubSpot Knowledge Base
I would like the possibility to integrate the HubSpot knowledge base as a source for my agent.
Patrick Wieczorek 5 months ago
Integrate the HubSpot Knowledge Base
I would like the possibility to integrate the HubSpot knowledge base as a source for my agent.
Patrick Wieczorek 5 months ago
Desktop Application (.NET)
I’d like to suggest adding support for a white-label desktop application, particularly for Windows workstations (.NET). Each Organization can download the Desktop Application and interact with their AI Assistant via the Desktop Application It would even be nice if it could be branded as well.
Zack Roberts 6 months ago
Desktop Application (.NET)
I’d like to suggest adding support for a white-label desktop application, particularly for Windows workstations (.NET). Each Organization can download the Desktop Application and interact with their AI Assistant via the Desktop Application It would even be nice if it could be branded as well.
Zack Roberts 6 months ago
