ClaudeSuperPower
SubmitLog in

aidp-semantic-model

Skill

Maintain a semantic grounding layer (.aidp/semantic.md) for AIDP — logical entity names, SQL-defined metrics, joins with cardinality, synonyms, and value dictionaries. Use when the user wants to define metrics/business terms, improve NL-to-SQL accuracy, standardize "revenue/customers/etc.", or set u

0Finance

Install

git clone https://github.com/oracle-samples/oracle-aidp-samples.git ~/.claude/skills/aidp-semantic-model

What is aidp-semantic-model?

Maintain a semantic grounding layer (.aidp/semantic.md) for AIDP — logical entity names, SQL-defined metrics, joins with cardinality, synonyms, and value dictionaries. Use when the user wants to define metrics/business terms, improve NL-to-SQL accuracy, standardize "revenue/customers/etc.", or set up a semantic model. Read by analyzing-data, verified-queries, profiling, and data-quality.

What this can do

Capabilities declared in this component's own frontmatter — not inferred.

Inherit all session tools

Declares no tool restrictions — inherits every session tool

~98 tokens of context used while enabled, before you invoke anything

Documentation

README · ~1 min read

aidp-semantic-model — the semantic grounding layer

Create and maintain .aidp/semantic.md: the business-meaning layer that grounds NL-to-SQL. This is the lever curated systems (Snowflake semantic model, Databricks Genie metrics/joins) rely on — without it, real-world NL-to-SQL accuracy is low.

When to use

  • Define metrics (revenue, active_customers, gross_margin…), logical names, joins, synonyms, or value sets.
  • The user wants consistent, reusable business semantics across questions.

Instruction hierarchy (most → least reliable)

  1. SQL expressions for metrics/filters (preferred).
  2. Example SQL for ambiguous prompts (store these via aidp-verified-queries).

Reviews

Log in to leave a review.

No reviews yet — be the first.

Explore related

Other things in this space — across every part of the ecosystem, not just skills.