monitor
KPI monitoring and issue proposal: analyze crash rates, store reviews, and metrics to suggest next priorities
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
القائمة
KPI monitoring and issue proposal: analyze crash rates, store reviews, and metrics to suggest next priorities
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Process issues sequentially: /dev per issue in isolated sub-agent → CI wait → merge → next
E2E development: investigate → dig → decompose → implement → test → review → PR
Break a task into ordered subtasks with dependencies
Investigate codebase for an issue in a forked context (context isolation)
Clarify ambiguities in plans with structured questions and auto-decide rules
Audit codebase for tech debt, code quality, and architecture issues — then create GitHub Issues
| name | monitor |
| description | KPI monitoring and issue proposal: analyze crash rates, store reviews, and metrics to suggest next priorities |
| user-invocable | true |
| disable-model-invocation | true |
| allowed-tools | ["Read","Grep","Glob","Agent","Bash(gh issue create:*)","Bash(gh issue list:*)","TaskCreate","TaskUpdate","TaskList","AskUserQuestion","ToolSearch"] |
Status: Proof of Concept — Requires Firebase MCP, Store API access, and analytics integration. This skill defines the target workflow for fully autonomous AI-driven operations.
Monitor project KPIs and propose next actions based on data.
user-feedback labelCollect and report on key metrics:
| Metric | Source | Threshold |
|---|---|---|
| Crash-free rate | Crashlytics | < 99.5% → Issue |
| D1 Retention | Analytics | < 40% → investigate |
| D7 Retention | Analytics | < 20% → investigate |
| D30 Retention | Analytics | < 10% → investigate |
| Feature usage rate | Analytics | < 5% → consider removal |
| Conversion rate | Store | declining → investigate |
Score potential features on two axes:
Axis 1: User Requests (Qualitative)
Axis 2: Metrics (Quantitative)
Rule: Only features where both axes align get proposed. Exception: crash/security fixes act on metrics alone.
For each recommended action:
gh issue create \
--title "{priority-label}: {concise description}" \
--body "{rationale with data points}" \
--label "ai-proposed,{priority}"
## KPI Monitor Report
**Date:** YYYY-MM-DD
**Period:** last 7 days
### Health
| Metric | Current | Trend | Status |
|---|---|---|---|
### Issues Created
| # | Title | Priority | Rationale |
|---|---|---|---|
### Recommended Next Actions
1. ...
2. ...