connect_tag

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

With no annotations provided, the description fully discloses behavioral aspects: it registers a Snowflake tag as a first-class ALTR object, creates a `tag_group_id` and masking configuration, and automatically resolves the friendly database name. It also lists related tools for inspection and editing, giving a complete picture of side effects.

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?

The description is well-structured: it opens with a clear purpose statement, then provides platform-specific guidance, explains workflow, and ends with a behavioral note. It is reasonably concise, though the Databricks advice is repeated slightly. Overall, it is front-loaded and efficient.

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 the tool's complexity and the lack of annotations, the description is complete. It explains the tool's role within the ALTR ecosystem, prerequisites, post-connection effects, and platform-specific behavior. The presence of an output schema (not shown but indicated) complements the description, making it fully informative for agent decision-making.

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?

Schema description coverage is 100%, so the baseline is 3. The description adds value by explaining that `database_name` is a friendly name from `get_databases` and that the tool auto-resolves it, but it does not elaborate on `schema_name` or `tag_name` beyond the schema. The added context is useful but not extensive.

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 the tool's purpose: connecting a Snowflake tag to ALTR for use in masking policies. It specifies the action (connect), the resource (Snowflake tag), and the intended use, effectively distinguishing it from sibling tools by explicitly stating it is Snowflake-only.

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?

The description provides explicit usage guidance: 'SNOWFLAKE ONLY — do NOT use for Databricks.' It explains why Databricks tags are not applicable and directs the agent to use `create_policy` instead. It also outlines prerequisites (tag must exist in Snowflake) and post-connection behavior, making when-to-use and when-not-to-use clear.

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