check-mr-feedback
Skill2 starsChanged 19 days agoApache-2.0View on GitHub
Check your open MRs for reviewer comments that need your attention. Scans for human comments (filters bots), meeting requests, code change requests, questions, approval status. Use when you want to see what feedback needs a response or before addressing review comments.
In this repository124 other files it gives its agents.
- add-projectSkill
- ansible-configure-vmSkill
- api-smoke-testSkill
- appinterface-checkSkill
- attach-session-to-jiraSkill
- aws-rds-debugSkill
- beerSkill
- bootstrap-all-knowledgeSkill
- bootstrap-knowledgeSkill
- build-persona-styleSkill
- cancel-pipelineSkill
- cert-checkSkill
- check-ci-healthSkill
- check-integration-testsSkill
- check-my-prsSkill
- check-secretsSkill
- ci-retrySkill
- cleanup-branchesSkill
- cleanup-stale-executionsSkill
- clone-jira-issueSkill
- close-issueSkill
- close-mrSkill
- cloud-inventorySkill
- coffeeSkill
- compare-optionsSkill
- create-jira-issueSkill
- create-mrSkill
- create-slide-deckSkill
- data-migration-verifySkill
- debug-local-dbSkill
- debug-prodSkill
- deploy-to-ephemeralSkill
- dev-workflow-orchestratorSkill
- discovered-work-summarySkill
- edit-slide-deckSkill
- email-digestSkill
- environment-overviewSkill
- explain-codeSkill
- export-presentationSkill
- extend-ephemeralSkill
- find-similar-codeSkill
- gather-contextSkill
- gdrive-researchSkill
- gke-cluster-opsSkill
- hello-worldSkill
- hotfixSkill
- inscope-researchSkill
- investigate-alertSkill
- investigate-service-issuesSkill
- investigate-slack-alertSkill
- jira-hygiene-allSkill
- jira-hygieneSkill
- knowledge-refreshSkill
- konflux-statusSkill
- learn-architectureSkill
- learn-patternSkill
- list-presentationsSkill
- local-build-testSkill
- local-dev-environmentSkill
- manage-local-servicesSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 2 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 40
Use split_mr_comments, is_bot_comment (shared parsers)
- Distinctive: line 60
Add follow-ups: "Respond to feedback on MR !X", "Schedule meeting for MR !X with Y"
- Distinctive: line 82
No pending feedback if clear
≈ “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
Check MR Feedback
Review your open MRs for feedback requiring response.
Inputs
| Input | Type | Default | Purpose |
project | string | automation-analytics/automation-analytics-backend | GitLab project |
create_meetings | bool | false | Create Google Meet invites for meeting requests |
mr_ids | array | - | Specific MR IDs (default: all open) |
slack_format | bool | false | Slack link format |
Workflow
1. Load Persona
persona_load("developer")
2. Check Known Issues
check_known_issues("gitlab_mr_list", "")
3. Get Open MRs
gitlab_mr_list(project, author="@me")— open MRs- Filter by
mr_idsif provided
4. Get Comments (up to 5 MRs)
gitlab_mr_comments(project, mr_id)for each MR
5. Analyze Comments
- Use
split_mr_comments,is_bot_comment(shared parsers) - Filter: human comments only, exclude own
- Detect: meeting requests (meeting, call, discuss, sync, chat, walk through)
- Detect: needs response (please, could you, ?, consider, suggest)
- Build:
{mr_id, title, comments, meeting_requests, needs_response}
6. Meeting Invites (if create_meetings)
- Check
google_calendarconfig - For each meeting request:
google_calendar_quick_meeting(title, attendee_email, when="auto") - Or suggest tool calls if not auto-creating
7. Format Summary
- Per MR: author, text, icon (💬/📅/❓)
- Meeting requests: suggest
google_calendar_find_meeting,google_calendar_quick_meeting
8. Memory
memory_session_log("Checked MR feedback", "{count} MRs with feedback")- Add follow-ups: "Respond to feedback on MR !X", "Schedule meeting for MR !X with Y"
9. Learn from Failures
- VPN:
learn_tool_fix("gitlab_mr_list", "no such host", "VPN", "vpn_connect()")
MCP Tools
persona_loadcheck_known_issuesgitlab_mr_listgitlab_mr_commentsgoogle_calendar_quick_meeting(if create_meetings)memory_session_logmemory_append(follow_ups)learn_tool_fix
Output
- MR Feedback Summary
- Per MR: comments with author, text, meeting/response flags
- Meeting scheduling suggestions
- No pending feedback if clear
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.

