monte-carlo-context-detection

When to Use

- Use when this upstream workflow matches the user's stated goal.

- Use when the task requires the procedures documented in this skill.

# Monte Carlo Context Detection

This skill determines which Monte Carlo skill or workflow best fits the user's current context. It activates reactively for ambiguous or multi-step data-related messages, gathers signals, and routes to the right skill or workflow.

> **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 file for signal definitions: `references/signal-definitions.md` (relative to this file). Read it before routing.

When to activate this skill

This skill is activated by the CLAUDE.md routing table when:

- The user's message relates to data quality, alerts, incidents, coverage, or Monte Carlo — but doesn't clearly match a single skill in the routing table

- The user's intent is ambiguous or could span multiple skills

- The user asks a broad question like "help me with my data" or "what's going on?"

When NOT to activate this skill

- A skill or workflow is already active in the conversation — the active skill owns the conversation, do not intercept

- The user's message clearly matches a single skill in the CLAUDE.md routing table — route directly, no need for context detection

- The user is editing a dbt model — defer to the `prevent` skill which auto-activates via hooks

- The user's message is not data-related at all

---

Workflow: Reactive Routing

This skill is purely reactive — it activates for ambiguous or multi-step data-related messages and routes them.

Follow these steps in order.

Step 0: Fast-path clear intent (stop early if matched)

Before doing anything else, check whether the user's message unambiguously matches a single existing skill. If so, **skip the rest of this workflow** and immediately load that skill — do NOT read `references/signal-definitions.md`, do NOT make API probes.

| Clear user intent | Skill to load immediately |

|---|---|

| "Check health of [named table]" / "status of [named table]" | `../asset-health/SKILL.md` |

| "Create a [monitor type] on [named table]" | `../monitoring-advisor/SKILL.md` |

| "Investigate alert on [named table]" / "why is [named table] stale/broken?" | `../incident-response/SKILL.md` |

| "What should I monitor?" / "where are my coverage gaps?" | `../proactive-monitoring/SKILL.md` |

| "Instrument my agent" / "set up Monte Carlo tracing on [named framework] agent" / "setting up an agent" | `../instrument-agent/SKILL.md` |

Context-detection is for **ambiguous** requests only. If the request is clear, routing through this skill wastes turns and tokens.

If no clear match, proceed to Step 1.

Step 1: Categorize intent

Read `references/signal-definitions.md` for the full signal catalog. Determine which category the user's message falls into:

| Category | Signals | Example messages |

|----------|---------|-----------------|

| **Specific asset** | User mentions a table name, or has a `.sql` model file open in their IDE | "what's wrong with stg_payments?", "check this table" |

| **Active incident** | Keywords: alert, broken, stale, failing, incident, triage, wrong data | "I have alerts firing", "data looks wrong", "something broke" |

| **Coverage/monitoring** | Keywords: monitor, coverage, gaps, unmonitored, what should I watch | "what should I monitor?", "where are my gaps?" |

| **Agent instrumentation** | Keywords: instrument, set up tracing, set up Monte Carlo tracing, setting up an agent. Often mentions