| name | deploy-check |
| description | [experimental] Evaluate deployment risk by analyzing code changes against incident history, active incidents, and on-call readiness. Forked-subagent flow may not have MCP access in all Claude Code contexts. |
| argument-hint | ["branch-name"] |
| disable-model-invocation | true |
| context | fork |
| agent | rootly:deploy-guardian |
| allowed-tools | ["Bash","mcp__rootly__*"] |
Pre-Deploy Safety Check (experimental)
Experimental: this skill uses context: fork to delegate to the deploy-guardian agent. In some Claude Code contexts the forked subagent does not inherit the plugin's MCP tools. If the agent reports MCP tools unavailable, run /rootly:status to manually check active incidents before deploying.
You are evaluating whether it is safe to deploy the current code changes. Follow this workflow carefully.
Current changes
!git diff --stat HEAD
Current branch
!git branch --show-current
Recent commits
!git log --oneline -5
Workflow
1. Assess Changes
Review the git diff output above. If the diff is empty (no changes), report "No changes to evaluate -- working tree is clean" and stop.
Identify which files and components are affected by the changes.
2. Resolve Affected Services
Determine which Rootly service(s) these changes map to, using this resolution chain (in priority order):
- Check
.claude/rootly-config.json in the project root -- if it exists, use the services field
- Match repo name: Use the git repo name (from
basename $(git rev-parse --show-toplevel)) to search for matching Rootly services via mcp__rootly__search_incidents
- Ask the user: If neither method works, ask which service(s) this repo maps to
3. Search Incident History
Call mcp__rootly__search_incidents for the identified services, looking at the last 90 days. Note any patterns in frequency, severity, or root causes.
4. Find Related Incidents
Call mcp__rootly__find_related_incidents with a summary of the current changes (based on the diff). This uses TF-IDF similarity matching to find historically similar incidents.
If results have confidence scores below 0.3, flag them as low confidence and note that manual review may be needed.
5. Check Active Incidents
Call mcp__rootly__search_incidents filtered to active (started) status for the affected services. Pay special attention to P1/P2 (critical/high severity) incidents.
6. Check On-Call Readiness
Call mcp__rootly__get_oncall_handoff_summary to verify:
- Who is currently on-call
- When the next handoff is
- Whether there are any on-call gaps
7. Synthesize Deployment Brief
Present a structured deployment brief:
## Deployment Safety Brief
**Risk Level**: [LOW / MEDIUM / HIGH / CRITICAL]
**Branch**: [branch name]
**Changed files**: [count]
### Active Incidents
[List any active incidents on affected services, or "None"]
### On-Call Status
- **Current**: [name] (since [time])
- **Next handoff**: [time]
- **Status**: [Available / Gap detected / High fatigue]
### Similar Past Incidents
[Top 3 similar incidents with what happened and how they were resolved]
### Risk Factors
[Bullet list of specific risks identified]
### Recommendation
**[GO / CAUTION / NO-GO]**: [1-2 sentence reasoning]
Risk level criteria:
- LOW: No active incidents, no similar past incidents, on-call is healthy
- MEDIUM: Minor past incidents found, or on-call handoff is imminent
- HIGH: Active incidents on related services, or recurring pattern of similar incidents
- CRITICAL: Active P1/P2 incident on the affected service, or significant on-call gaps
