Dictionnaire de métriques

Parcourez et affichez les définitions de métriques du dataset actif. Accédez rapidement aux formules, unités et validations de chaque métrique.

Spar Skills Guide Bot
Data & IAIntermédiaire1 vues0 installations28/02/2026
Claude CodeCursorWindsurfCopilot
metricsdata-dictionaryanalyticsyaml-parsingsearch

Skill: Metrics

Purpose

Browse, search, and display metric definitions from the active dataset's metric dictionary. Provides quick access to how metrics are defined, computed, and validated.

When to Use

  • User says /metrics or "show me the metrics" or "what metrics do we track?"
  • During analysis, to confirm a metric's definition before computing it
  • When writing a metric spec, to check for existing definitions

Invocation

/metrics — list all metrics for the active dataset /metrics {id} — show full spec for a specific metric /metrics category={cat} — filter by category (e.g., monetization) /metrics search={term} — search metric names and descriptions

Instructions

Step 1: Load Metric Dictionary

  1. Read .knowledge/active.yaml to identify the active dataset.
  2. Read .knowledge/datasets/{active}/metrics/index.yaml for the metric list.
  3. If no metrics directory exists: "No metric dictionary for this dataset. Use the metric-spec skill to define metrics."

Step 2: Execute Command

List all (/metrics):

  • Display as a table: id, name, category, direction, validation_status
  • Group by category
  • Show total count

Show specific (/metrics {id}):

  • Read .knowledge/datasets/{active}/metrics/{id}.yaml
  • Display: name, category, owner, full definition (formula, unit, direction, granularity), source tables, dimensions, guardrails, typical range, validation status
  • If metric not found: suggest closest match from index

Filter by category (/metrics category=monetization):

  • Filter index by category field
  • Display filtered table

Search (/metrics search=revenue):

  • Search metric names and descriptions (case-insensitive substring)
  • Display matching metrics

Step 3: Contextual Suggestions

After displaying metrics, suggest relevant actions:

  • "Want to validate {metric} against the current data? Use the data-profiling skill."
  • "Need to define a new metric? Use the metric-spec skill."
  • "Want to see how {metric} trends over time? Ask me to analyze it."

Edge Cases

  • No active dataset: Prompt to connect one
  • Empty metric dictionary: Suggest using metric-spec skill
  • Metric referenced but not in dictionary: Offer to create it
  • Stale validation: Flag metrics where last_validated is >30 days ago

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