nx-ci-monitor▌
tech-leads-club/agent-skills · updated May 23, 2026
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Monitor Nx Cloud CI pipeline status and handle self-healing fixes automatically. Use when user says "watch CI", "monitor pipeline", "check CI status", "fix CI failures", or "self-heal CI". Requires Nx Cloud connection. Do NOT use for local task execution (use nx-run-tasks) or general CI debugging outside Nx Cloud.
| name | nx-ci-monitor |
| description | Monitor Nx Cloud CI pipeline status and handle self-healing fixes automatically. Use when user says "watch CI", "monitor pipeline", "check CI status", "fix CI failures", or "self-heal CI". Requires Nx Cloud connection. Do NOT use for local task execution (use nx-run-tasks) or general CI debugging outside Nx Cloud. |
CI Monitor Command
You are the orchestrator for monitoring Nx Cloud CI pipeline executions and handling self-healing fixes. You spawn the ci-watcher subagent to poll CI status and make decisions based on the results.
Context
- Current Branch: !
git branch --show-current - Current Commit: !
git rev-parse --short HEAD - Remote Status: !
git status -sb | head -1
User Instructions
$ARGUMENTS
Important: If user provides specific instructions, respect them over default behaviors described below.
Configuration Defaults
| Setting | Default | Description |
|---|---|---|
--max-cycles | 10 | Maximum CIPE cycles before timeout |
--timeout | 120 | Maximum duration in minutes |
--verbosity | medium | Output level: minimal, medium, verbose |
--branch | (auto-detect) | Branch to monitor |
--subagent-timeout | 60 | Subagent polling timeout in minutes |
--fresh | false | Ignore previous context, start fresh |
--auto-fix-workflow | false | Attempt common fixes for pre-CIPE failures (e.g., lockfile updates) |
--new-cipe-timeout | 10 | Minutes to wait for new CIPE after action |
--local-verify-attempts | 3 | Max local verification + enhance cycles before pushing to CI |
Parse any overrides from $ARGUMENTS and merge with defaults.
Nx Cloud Connection Check
CRITICAL: Before starting the monitoring loop, verify the workspace is connected to Nx Cloud.
Step 0: Verify Nx Cloud Connection
-
Check
nx.jsonat workspace root fornxCloudIdornxCloudAccessToken -
If
nx.jsonmissing OR neither property exists → exit with:[ci-monitor] Nx Cloud not connected. Unlock 70% faster CI and auto-fix broken PRs with https://nx.dev/nx-cloud -
If connected → continue to main loop
Session Context Behavior
Important: Within a Claude Code session, conversation context persists. If you Ctrl+C to interrupt the monitor and re-run /ci-monitor, Claude remembers the previous state and may continue from where it left off.
- To continue monitoring: Just re-run
/ci-monitor(context is preserved) - To start fresh: Use
/ci-monitor --freshto ignore previous context - For a completely clean slate: Exit Claude Code and restart
claude
Default Behaviors by Status
The subagent returns with one of the following statuses. This table defines the default behavior for each status. User instructions can override any of these.
| Status | Default Behavior |
|---|---|
ci_success | Exit with success. Log "CI passed successfully!" |
fix_auto_applying | Fix will be auto-applied by self-healing. Do NOT call MCP. Record last_cipe_url, spawn new subagent in wait mode to poll for new CIPE. |
fix_available | Compare failedTaskIds vs verifiedTaskIds to determine verification state. See Fix Available Decision Logic section below. |
fix_failed | Self-healing failed to generate fix. Attempt local fix based on taskOutputSummary. If successful → commit, push, loop. If not → exit with failure. |
environment_issue | Call MCP to request rerun: update_self_healing_fix({ shortLink, action: "RERUN_ENVIRONMENT_STATE" }). New CIPE spawns automatically. Loop to poll for new CIPE. |
no_fix | CI failed, no fix available (self-healing disabled or not executable). Attempt local fix if possible. Otherwise exit with failure. |
no_new_cipe | Expected CIPE never spawned (CI workflow likely failed before Nx tasks). Report to user, attempt common fixes if configured, or exit with guidance. |
polling_timeout | Subagent polling timeout reached. Exit with timeout. |
cipe_canceled | CIPE was canceled. Exit with canceled status. |
cipe_timed_out | CIPE timed out. Exit with timeout status. |
error | Increment no_progress_count. If >= 3 → exit with circuit breaker. Otherwise wait 60s and loop. |
Fix Available Decision Logic
When subagent returns fix_available, main agent compares failedTaskIds vs verifiedTaskIds:
Step 1: Categorize Tasks
- Verified tasks = tasks in both
failedTaskIdsANDverifiedTaskIds - Unverified tasks = tasks in
failedTaskIdsbut NOT inverifiedTaskIds - E2E tasks = unverified tasks where target contains "e2e" (task format:
<project>:<target>or<project>:<target>:<config>) - Verifiable tasks = unverified tasks that are NOT e2e
Step 2: Determine Path
| Condition | Path |
|---|---|
| No unverified tasks (all verified) | Apply via MCP |
| Unverified tasks exist, but ALL are e2e | Apply via MCP (treat as verified enough) |
| Verifiable tasks exist | Local verification flow |
Step 3a: Apply via MCP (fully/e2e-only verified)
- Call
update_self_healing_fix({ shortLink, action: "APPLY" }) - Record
last_cipe_url, spawn subagent in wait mode
Step 3b: Local Verification Flow
When verifiable (non-e2e) unverified tasks exist:
-
Detect package manager:
pnpm-lock.yamlexists →pnpm nxyarn.lockexists →yarn nx- Otherwise →
npx nx
-
Run verifiable tasks in parallel:
- Spawn
generalsubagents to run each task concurrently - Each subagent runs:
<pm> nx run <taskId> - Collect pass/fail results from all subagents
- Spawn
-
Evaluate results:
| Result | Action |
|---|---|
| ALL verifiable tasks pass | Apply via MCP |
| ANY verifiable task fails | Apply-locally + enhance flow |
-
Apply-locally + enhance flow:
- Run
nx apply-locally <shortLink> - Enhance the code to fix failing tasks
- Run failing tasks again to verify fix
- If still failing → increment
local_verify_count, loop back to enhance - If passing → commit and push, record
expected_commit_sha, spawn subagent in wait mode
- Run
-
Track attempts (wraps step 4):
- Increment
local_verify_countafter each enhance cycle - If
local_verify_count >= local_verify_attempts(default: 3):-
Get code in commit-able state
-
Commit and push with message indicating local verification failed
-
Report to user:
[ci-monitor] Local verification failed after <N> attempts. Pushed to CI for final validation. Failed: <taskIds> -
Record
expected_commit_sha, spawn subagent in wait mode (let CI be final judge)
-
- Increment
Commit Message Format
git commit -m "fix(<projects>): <brief description>
Failed tasks: <taskId1>, <taskId2>
Local verification: passed|enhanced|failed-pushing-to-ci"
Unverified Fix Flow (No Verification Attempted)
When verificationStatus is FAILED, NOT_EXECUTABLE, or fix has couldAutoApplyTasks != true with no verification:
- Analyze fix content (
suggestedFix,suggestedFixReasoning,taskOutputSummary) - If fix looks correct → apply via MCP
- If fix needs enhancement → use Apply Locally + Enhance Flow above
- If fix is wrong → reject via MCP, fix from scratch, commit, push
Auto-Apply Eligibility
The couldAutoApplyTasks field indicates whether the fix is eligible for automatic application:
true: Fix is eligible for auto-apply. Subagent keeps polling while verification is in progress. Returnsfix_auto_applyingwhen verified, orfix_availableif verification fails.falseornull: Fix requires manual action (apply via MCP, apply locally, or reject)
Key point: When subagent returns fix_auto_applying, do NOT call MCP to apply - self-healing handles it. Just spawn a new subagent in wait mode.
Apply vs Reject vs Apply Locally
- Apply via MCP: Calls
update_self_healing_fix({ shortLink, action: "APPLY" }). Self-healing agent applies the fix in CI and a new CIPE spawns automatically. No local git operations needed. - Apply Locally: Runs
nx apply-locally <shortLink>. Applies the patch to your local working directory and sets state toAPPLIED_LOCALLY. Use this when you want to enhance the fix before pushing. - Reject via MCP: Calls
update_self_healing_fix({ shortLink, action: "REJECT" }). Marks fix as rejected. Use only when the fix is completely wrong and you'll fix from scratch.
Apply Locally + Enhance Flow
When the fix needs enhancement (use nx apply-locally, NOT reject):
-
Apply the patch locally:
nx apply-locally <shortLink>(this also updates state toAPPLIED_LOCALLY) -
Make additional changes as needed
-
Commit and push:
git add -A git commit -m "fix: resolve <failedTaskIds>" git push origin $(git branch --show-current) -
Loop to poll for new CIPE
Reject + Fix From Scratch Flow
When the fix is completely wrong:
-
Call MCP to reject:
update_self_healing_fix({ shortLink, action: "REJECT" }) -
Fix the issue from scratch locally
-
Commit and push:
git add -A git commit -m "fix: resolve <failedTaskIds>" git push origin $(git branch --show-current) -
Loop to poll for new CIPE
Environment Issue Handling
When failureClassification == 'ENVIRONMENT_STATE':
- Call MCP to request rerun:
update_self_healing_fix({ shortLink, action: "RERUN_ENVIRONMENT_STATE" }) - New CIPE spawns automatically (no local git operations needed)
- Loop to poll for new CIPE with
previousCipeUrlset
No-New-CIPE Handling
When status == 'no_new_cipe':
This means the expected CIPE was never created - CI likely failed before Nx tasks could run.
-
Report to user:
[ci-monitor] No CI attempt for <sha> after 10 min. Check CI provider for pre-Nx failures (install, checkout, auth). Last CI attempt: <previousCipeUrl> -
If user configured auto-fix attempts (e.g.,
--auto-fix-workflow):-
Detect package manager: check for
pnpm-lock.yaml,yarn.lock,package-lock.json -
Run install to update lockfile:
pnpm install # or npm install / yarn install -
If lockfile changed:
git add pnpm-lock.yaml # or appropriate lockfile git commit -m "chore: update lockfile" git push origin $(git branch --show-current) -
Record new commit SHA, loop to poll with
expectedCommitSha
-
-
Otherwise: Exit with
no_new_cipestatus, providing guidance for user to investigate
Exit Conditions
Exit the monitoring loop when ANY of these conditions are met:
| Condition | Exit Type |
|---|---|
CI passes (cipeStatus == 'SUCCEEDED') | Success |
| Max CIPE cycles reached | Timeout |
| Max duration reached | Timeout |
| 3 consecutive no-progress iterations | Circuit breaker |
| No fix available and local fix not possible | Failure |
| No new CIPE and auto-fix not configured | Pre-CIPE failure |
| User cancels | Cancelled |
Main Loop
Step 1: Initialize Tracking
cycle_count = 0
start_time = now()
no_progress_count = 0
local_verify_count = 0
last_state = null
last_cipe_url = null
expected_commit_sha = null
Step 2: Spawn Subagent
Spawn the ci-watcher subagent to poll CI status:
Fresh start (first spawn, no expected CIPE):
Task(
agent: "ci-watcher",
prompt: "Monitor CI for branch '<branch>'.
Subagent timeout: <subagent-timeout> minutes.
New-CIPE timeout: <new-cipe-timeout> minutes.
Verbosity: <verbosity>."
)
After action that triggers new CIPE (wait mode):
Task(
agent: "ci-watcher",
prompt: "Monitor CI for branch '<branch>'.
Subagent timeout: <subagent-timeout> minutes.
New-CIPE timeout: <new-cipe-timeout> minutes.
Verbosity: <verbosity>.
WAIT MODE: A new CIPE should spawn. Ignore old CIPE until new one appears.
Expected commit SHA: <expected_commit_sha>
Previous CIPE URL: <last_cipe_url>"
)
Step 3: Handle Subagent Response
When subagent returns:
- Check the returned status
- Look up default behavior in the table above
- Check if user instructions override the default
- Execute the appropriate action
- If action expects new CIPE, update tracking (see Step 3a)
- If action results in looping, go to Step 2
Step 3a: Track State for New-CIPE Detection
After actions that should trigger a new CIPE, record state before looping:
| Action | What to Track | Subagent Mode |
|---|---|---|
| Fix auto-applying | last_cipe_url = current cipeUrl | Wait mode |
| Apply via MCP | last_cipe_url = current cipeUrl | Wait mode |
| Apply locally + push | expected_commit_sha = $(git rev-parse HEAD) | Wait mode |
| Reject + fix + push | expected_commit_sha = $(git rev-parse HEAD) | Wait mode |
| Fix failed + local fix + push | expected_commit_sha = $(git rev-parse HEAD) | Wait mode |
| No fix + local fix + push | expected_commit_sha = $(git rev-parse HEAD) | Wait mode |
| Environment rerun | last_cipe_url = current cipeUrl | Wait mode |
| No-new-CIPE + auto-fix + push | expected_commit_sha = $(git rev-parse HEAD) | Wait mode |
CRITICAL: When passing expectedCommitSha or last_cipe_url to the subagent, it enters wait mode:
- Subagent will completely ignore the old/stale CIPE
- Subagent will only wait for new CIPE to appear
- Subagent will NOT return to main agent with stale CIPE data
- Once new CIPE detected, subagent switches to normal polling
Why wait mode matters for context preservation: Stale CIPE data can be very large (task output summaries, suggested fix patches, reasoning). If subagent returns this to main agent, it pollutes main agent's context with useless data since we already processed that CIPE. Wait mode keeps stale data in the subagent, never sending it to main agent.
Step 4: Progress Tracking
After each action:
- If state changed significantly → reset
no_progress_count = 0 - If state unchanged →
no_progress_count++ - On new CI attempt detected → reset
local_verify_count = 0
Status Reporting
Based on verbosity level:
| Level | What to Report |
|---|---|
minimal | Only final result (success/failure/timeout) |
medium | State changes + periodic updates ("Cycle N | Elapsed: Xm | Status: ...") |
verbose | All of medium + full subagent responses, git outputs, MCP responses |
User Instruction Examples
Users can override default behaviors:
| Instruction | Effect |
|---|---|
| "never auto-apply" | Always prompt before applying any fix |
| "always ask before git push" | Prompt before each push |
| "reject any fix for e2e tasks" | Auto-reject if failedTaskIds contains e2e |
| "apply all fixes regardless of verification" | Skip verification check, apply everything |
| "if confidence < 70, reject" | Check confidence field before applying |
| "run 'nx affected -t typecheck' before applying" | Add local verification step |
| "auto-fix workflow failures" | Attempt lockfile updates on pre-CIPE failures |
| "wait 45 min for new CIPE" | Override new-CIPE timeout (default: 10 min) |
Error Handling
| Error | Action |
|---|---|
| Git rebase conflict | Report to user, exit |
nx apply-locally fails | Report to user, attempt manual patch or exit |
| MCP tool error | Retry once, if fails report to user |
| Subagent spawn failure | Retry once, if fails exit with error |
| No new CIPE detected | If --auto-fix-workflow, try lockfile update; otherwise report to user with guidance |
| Lockfile auto-fix fails | Report to user, exit with guidance to check CI logs |
Example Session
Example 1: Normal Flow with Self-Healing (medium verbosity)
[ci-monitor] Starting CI monitor for branch 'feature/add-auth'
[ci-monitor] Config: max-cycles=5, timeout=120m, verbosity=medium
[ci-monitor] Spawning subagent to poll CI status...
[CI Monitor] CI attempt: IN_PROGRESS | Self-Healing: NOT_STARTED | Elapsed: 1m
[CI Monitor] CI attempt: FAILED | Self-Healing: IN_PROGRESS | Elapsed: 3m
[CI Monitor] CI attempt: FAILED | Self-Healing: COMPLETED | Elapsed: 5m
[ci-monitor] Fix available! Verification: COMPLETED
[ci-monitor] Applying fix via MCP...
[ci-monitor] Fix applied in CI. Waiting for new CI attempt...
[ci-monitor] Spawning subagent to poll CI status...
[CI Monitor] New CI attempt detected!
[CI Monitor] CI attempt: SUCCEEDED | Elapsed: 8m
[ci-monitor] CI passed successfully!
[ci-monitor] Summary:
- Total cycles: 2
- Total time: 12m 34s
- Fixes applied: 1
- Result: SUCCESS
Example 2: Pre-CI Failure (medium verbosity)
[ci-monitor] Starting CI monitor for branch 'feature/add-products'
[ci-monitor] Config: max-cycles=5, timeout=120m, auto-fix-workflow=true
[ci-monitor] Spawning subagent to poll CI status...
[CI Monitor] CI attempt: FAILED | Self-Healing: COMPLETED | Elapsed: 2m
[ci-monitor] Applying fix locally, enhancing, and pushing...
[ci-monitor] Committed: abc1234
[ci-monitor] Spawning subagent to poll CI status...
[CI Monitor] Waiting for new CI attempt... (expected SHA: abc1234)
[CI Monitor] ⚠️ CI attempt timeout (10 min). Returning no_new_cipe.
[ci-monitor] Status: no_new_cipe
[ci-monitor] --auto-fix-workflow enabled. Attempting lockfile update...
[ci-monitor] Lockfile updated. Committed: def5678
[ci-monitor] Spawning subagent to poll CI status...
[CI Monitor] New CI attempt detected!
[CI Monitor] CI attempt: SUCCEEDED | Elapsed: 18m
[ci-monitor] CI passed successfully!
[ci-monitor] Summary:
- Total cycles: 3
- Total time: 22m 15s
- Fixes applied: 1 (self-healing) + 1 (lockfile)
- Result: SUCCESS
How to use nx-ci-monitor on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add nx-ci-monitor
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches nx-ci-monitor from GitHub repository tech-leads-club/agent-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate nx-ci-monitor. Access the skill through slash commands (e.g., /nx-ci-monitor) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.4★★★★★66 reviews- ★★★★★Dhruvi Jain· Dec 28, 2024
nx-ci-monitor reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Soo Park· Dec 24, 2024
Useful defaults in nx-ci-monitor — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Xiao Nasser· Dec 20, 2024
We added nx-ci-monitor from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Ama Wang· Dec 12, 2024
I recommend nx-ci-monitor for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Oshnikdeep· Nov 19, 2024
I recommend nx-ci-monitor for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Ama Thomas· Nov 15, 2024
Registry listing for nx-ci-monitor matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Soo Singh· Nov 3, 2024
nx-ci-monitor reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Xiao Farah· Nov 3, 2024
nx-ci-monitor fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Dev Gonzalez· Oct 22, 2024
Registry listing for nx-ci-monitor matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Diya Choi· Oct 22, 2024
We added nx-ci-monitor from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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