Reading Data Dict
ClineOfficialPublished by Cline
- Skill
- Research and analysis
- Data and AI
- Apache-2.0
- No issues found
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill provides a structured procedure for locating and extracting data definitions from project documentation, such as dbt manifests, data dictionaries, and metric YAML files. It ensures that analytics SQL is built upon established business and product definitions rather than assumptions, helping to maintain consistency in metrics and data modeling.
What it does
- Locates documentation sources including dbt projects, data dictionaries, and metric files.
- Extracts key metadata such as metric names, populations, grains, and required columns.
- Prioritizes curated models over raw event tables for data analysis.
- Cross-references lineage and documentation to ensure accurate interpretation.
- Surfaces discrepancies between documentation and observed schema.
- Provides a standardized template for summarizing data definitions.
When to use it
- Before writing new analytics SQL queries.
- When mapping business terms to specific database models and columns.
- When resolving ambiguous metrics like active users, revenue, or retention.
- When verifying the grain, filters, or join keys of a data model.
Advantages
- Reduces reliance on assumptions when interpreting data.
- Promotes the use of curated, documented models.
- Standardizes the communication of data definitions to users.
- Identifies potential conflicts between documentation and actual data structures.
Usage examples
- “What is the definition of daily active users in our project?”
- The agent searches the dbt manifest and data dictionary to provide the official metric definition, grain, and the specific model used for calculation.
- “Which table should I use to calculate monthly recurring revenue?”
- The agent identifies the relevant curated model, lists the required columns, and summarizes any known caveats or filters associated with the metric.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/cline/reading-data-dict/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip reading-data-dict.zip -d .agents/skills
Documentation by Cline
Reading Data Dictionary
Use this before writing SQL for documented metrics, so that business and product terms map to the right models, columns, and definitions instead of guesses.
When invoked from the elicitation flow to resolve specific LOOK UP terms, scope the work to those terms: resolve their definitions and surface any options/candidates back to the user. Do not perform a full data exploration unless the user explicitly asked for one or no curated model is obvious.
Where the definitions live
This skill is generic. A project may document its data in one or more of:
a dbt project (model
.sql,models/**/*.yml,target/manifest.json, generated docs)a dedicated data dictionary directory (for example
data_dictionary/**)metric or semantic-model YAML files
a BI tool's metric layer, a wiki, or a README
If your team has a canonical source (for example a dbt repository), treat it as the source of truth and point this skill at it. Prefer reading it over the remote gh API or a fresh checkout rather than relying on a possibly-stale local clone.
Useful artifacts to inspect first, when present:
data_dictionary/**target/manifest.jsonmodels/**/*.ymlmodels/**/*.sqlmetric or semantic model YAML files
Procedure
Locate the documentation source, stopping at the first that works:
Canonical docs repo (preferred). If the team has one, read files directly without cloning. With the
ghCLI:# List a directory gh api repos/<org>/<dbt-repo>/contents/data_dictionary # Read a specific file gh api repos/<org>/<dbt-repo>/contents/data_dictionary/some-file.md \ --jq '.content' | base64 -dFetch
data_dictionary/**files selectively before any model SQL or YAMLs.Local clone (fallback). If
ghis unavailable or unauthenticated, check for a local directory whosegit remote -vmatches the canonical repo. Use it only if it is sufficiently up to date.ClickHouse schema fallback. If no documentation source is available, discover the schema directly (see
../clickhouse/). Prefer curated models (commonly namedgold_*,silver_*,fct_*,dim_*) over raw event or log tables. State explicitly that you fell back to the live schema and have no documented definition.
Inspect relevant
data_dictionary/**files first, then locate models, model docs, manifest entries, column descriptions, lineage, or metric docs for the requested concept.Identify the curated model first. Use raw event tables only when no curated model exists, the curated model is insufficient, or the user explicitly requests raw data.
Extract the exact definitions for:
metric name
entity/population
grain and time window
filters and exclusions
required columns
safe join keys/patterns
freshness, rollout, or coverage caveats
Cross-check lineage when the model is derived from raw events.
Summarize definitions back to the user when they affect interpretation.
If no relevant data dictionary entry exists, say so explicitly and continue with model docs, manifest metadata, and SQL lineage. If the data dictionary conflicts with model docs or the observed schema, surface the discrepancy before writing SQL.
Definition summary template
Definitions used:
- Metric: ...
- Population: ...
- Grain/window: ...
- Model/table: ...
- Key columns: ...
- Joins: ...
- Known caveats: ...Bias toward documented semantics
If a term like "active user," "daily active," "tokens," "revenue," "timeout," "telemetry," "retention," or "funnel" appears, do not invent a definition. Find a documented definition or ask the user to choose one.
Files
- ATTRIBUTION.mdAdded by AutoGineer860 B
- LICENSELicence file added by AutoGineer10.5 KiB
- SKILL.md3.9 KiB
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Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs a command-line tool
Security
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Attribution and licence
- Published by
- Cline
- Publisher
- Cline (Official)
- Source
- cline/skills · skills/data-analyst/skills/reading-data-dict · commit 2637846
- Licence
- Apache License 2.0 (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
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