discord-community-feedback
Skill180 starsChanged 8 months agoMITView on GitHub
Monitor Discord community channel for user-reported bugs and issues
In this repository13 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- cloudflare-cliSkill
- create-prSkill
- hosted-studio-debugSkill
- integration-testsSkill
- linear-issue-fixerSkill
- manage-api-keysSkill
- manage-tiersSkill
- sentry-issue-fixerSkill
- setupSkill
- studio-dbSkill
- unit-testsSkill
The file
We split this skill into the rules it gives an agent
7 rules. About 0 are common, 5 are distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈5
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 24
Use the Discord MCP read-messages tool to fetch recent messages:
- Distinctive: line 34
When reviewing messages, look for these indicators of issues:
- Distinctive: line 38
Functionality: not working, doesn't work, can't, unable, stuck
- Distinctive: line 70
If a user reports an issue that might be related to the hosted environment:
- Very specific: line 73
Use hosted-studio-debug skill to check logs around that time
- Distinctive: line 74
Look for correlating errors in consensus-worker or jsonrpc logs
- Distinctive: line 83
When summarizing community feedback:
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Discord Community Feedback Skill
Monitor the GenLayer Discord community feedback channel for user-reported bugs, issues, and problems.
Prerequisites
- Discord MCP server configured and running (discordmcp)
- Bot added to the GenLayer Discord server with read permissions
Channel Information
| Field | Value |
| Server ID | 1237055789441487021 |
| Channel ID | 1237114454877929482 |
Quick Commands
Use the Discord MCP read-messages tool to fetch recent messages:
Tool: read-messages
Channel: 1237114454877929482
Limit: 100 (max allowed)Identifying User Problems
When reviewing messages, look for these indicators of issues:
Problem Keywords
- Errors: error, bug, broken, crash, fail, exception
- Functionality: not working, doesn't work, can't, unable, stuck
- Help requests: help, issue, problem, wrong, weird
- Performance: slow, timeout, hang, freeze, unresponsive
Common User-Reported Issues
| Category | Example Patterns | Related Component |
| Transaction failures | "tx failed", "transaction stuck" | consensus-worker |
| Contract errors | "contract not deploying", "execution error" | genvm, consensus-worker |
| UI issues | "page not loading", "button doesn't work" | frontend |
| API errors | "RPC error", "connection failed" | jsonrpc |
| Wallet issues | "can't connect wallet", "balance wrong" | frontend, jsonrpc |
Workflow
- Fetch recent messages from the feedback channel (up to 100)
- Scan for problem indicators using keywords above
- Categorize issues by component (frontend, backend, consensus, etc.)
- Cross-reference with logs using the
hosted-studio-debugskill if needed - Summarize findings for the team
Triage Priority
| Priority | Indicators |
| High | Multiple users reporting same issue, "everything broken", data loss |
| Medium | Single user with reproducible issue, feature not working |
| Low | Questions, minor UI glitches, feature requests |
Integration with Hosted Studio Debug
If a user reports an issue that might be related to the hosted environment:
- Note the approximate time of the user's report
- Use
hosted-studio-debugskill to check logs around that time - Look for correlating errors in consensus-worker or jsonrpc logs
# Example: Check for errors around the time of a user report
argocd app logs studio-prd-workload --name studio-consensus-worker --tail 500 2>&1 | grep -iE "(error|exception|timeout)"Response Template
When summarizing community feedback:
## Community Feedback Summary
**Period**: [time range of messages reviewed]
**Total Messages**: [count]
**Issues Identified**: [count]
### High Priority
- [Issue description] - Reported by [count] users
### Medium Priority
- [Issue description]
### Low Priority / Questions
- [Description]
### No Issues
[If no problems found, note this]Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

