snapshot_models

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. It explains the mechanism: dbt compares source data, identifies changes, inserts new rows with validity timestamps, and closes original rows. This gives good behavioral insight, but could also mention idempotency or side effects like potential data duplication on reruns.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with sections: intro, 'When to use', 'How it works', Args, Returns, and Examples. Front-loaded with purpose. While slightly lengthy, every section adds value. Could be slightly more concise in the 'How it works' explanation, but overall effective.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and low schema coverage, the description provides sufficient context: usage guidelines, mechanism, parameter explanations, and examples. Output schema exists, so the brief return description is adequate. It covers the essential aspects for effective tool invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema has 0% description coverage, but the description compensates by explaining 'select' as dbt selector syntax with examples (e.g., 'snapshot_name', 'tag:daily') and 'exclude' as 'Exclude specific snapshots'. Examples further clarify usage. The description adds significant meaning beyond the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it 'snapshot models' and 'capture historical changes - SCD Type 2', with a detailed explanation of tracking slowly changing dimensions. This effectively distinguishes it from siblings like 'run_models' or 'build_models' which handle regular model execution.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Includes a 'When to use' section that specifies 'to track changes in slowly changing dimensions (SCD Type 2)'. It does not explicitly say when not to use or mention alternatives, but the context of sibling tool names provides implied differentiation. Additional exclusions would improve it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.