monte-carlo-performance-diagnosis
Diagnoses pipeline performance issues -- slow jobs, expensive queries, latency trends -- using Monte Carlo's cross-platform observability. Uses a tiered investigation approach: discover problems, bridge to affected tables, then drill into root causes. Activates when a user asks about...
Profile →npx skills add sickn33/agentic-awesome-skills --skill monte-carlo-performance-diagnosis --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Monte Carlo Performance Diagnosis Skill This skill helps diagnose data pipeline performance issues using Monte Carlo's cross-platform observability data. It works across Airflow, dbt, Databricks, and warehouse query engines to find bottlenecks, detect regressions, and identify root causes. > **Monte Carlo tool routing (required):** Always call Monte Carlo MCP tools through this plugin's > bundled server, whose fully-qualified tool names are > `mcp__plugin_mc-agent-toolkit_monte-carlo-mcp__<tool>` (e.g. > `mcp__plugin_mc-agent-toolkit_monte-carlo-mcp__get_alerts`). Bare tool names used in this skill > (`get_alerts`, `search`, `get_table`, …) refer to that bundled server. If the session also has a > separately-configured `monte-carlo-mcp` server, do **not** route to it — it may point at a > different endpoint or credentials. Reference files live next to this skill file. **Use the Read tool** (not MCP resources) to access them: - Tiered investigation approach: `references/investigation-tiers.md` (relative to this file) - Query analysis patterns: `references/query-analysis.md` (relative to this file) ## When to activate this skill Activate when the user: - Asks about slow pipelines,
- When to activate this skill
- When NOT to activate this skill
- Prerequisites
- Workflow
- Step 1: Identify the scope
- Step 2: Tier 1 -- Discovery
- Step 3: Bridge -- Job to Tables
- Step 4: Tier 2 -- Diagnosis
- Step 5: Present findings
- Important rules
- Limitations
What does the monte-carlo-performance-diagnosis skill do?
Diagnoses pipeline performance issues -- slow jobs, expensive queries, latency trends -- using Monte Carlo's cross-platform observability. Uses a tiered investigation approach: discover problems, bridge to affected tables, then drill into root causes. Activates when a user asks about...
How do I install it?
Run `npx skills add sickn33/agentic-awesome-skills --skill monte-carlo-performance-diagnosis --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From sickn33/agentic-awesome-skills, a repository with 44,414 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.