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ALTR MCP Server

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by altrsoftware

search_query_audits

Search Snowflake query audits using filters like tags, columns, users, and roles to find tag-based or column-based masking events. Returns a search identifier for retrieving results later.

Instructions

Search Snowflake query audits (tag and column masking).

Triggers an async search and returns a search_uuid (valid 30 days). Use get_query_audit_results with the search_uuid to retrieve results. All filters are combined with AND logic.

Use this for Snowflake tag-based or column-based masking audits. For sidecar proxy audits, use search_audits instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results (default 10000, max 100000).
offsetNoSkip this many results.
from_date_timeNoRFC3339 UTC start time (e.g. "2025-01-01T00:00:00Z").
to_date_timeNoRFC3339 UTC end time.
executing_roleNoFilter by role executing the query (case-insensitive).
executing_userNoFilter by user executing the query (case-insensitive).
query_idNoFilter by query identifier (case-insensitive).
policy_tag_nameNoFilter by policy tag name (case-insensitive).
policy_tag_valueNoFilter by policy tag value (case-insensitive).
policy_column_database_nameNoFilter by database name (case-insensitive).
policy_column_schema_nameNoFilter by schema name (case-insensitive).
policy_column_table_nameNoFilter by table name (case-insensitive).
policy_column_nameNoFilter by column name (case-insensitive).
order_byNo"asc" or "desc" (default "desc").
sort_byNo"event_time" or "rows_accessed" (default "event_time").

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses that the search is async, returns a search_uuid valid for 30 days, and that results are retrieved via a follow-up call. It does not mention rate limits, authentication needs, or failure modes, but the core async behavior is well explained.

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

Conciseness5/5

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

The description is very concise, using three short paragraphs. Each sentence adds essential information: purpose, async nature, follow-up instruction, filter logic, and sibling differentiation. No wasted words.

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

Completeness4/5

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

Given the 15 parameters and async nature, the description covers the main workflow and filter semantics. It does not detail error handling or timeout, but with an output schema present (not shown), the return format is presumably documented. The description is sufficient for an agent to use the tool correctly.

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

Parameters4/5

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

Schema coverage is 100% with each parameter having a description. The description adds valuable context that all filters are combined with AND logic, which clarifies how multiple parameters interact. This goes beyond what the schema provides.

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

Purpose5/5

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

The description clearly states the tool searches Snowflake query audits specifically for tag and column masking. It uses a specific verb 'Search' and identifies the resource 'Snowflake query audits'. It distinguishes from the sibling tool 'search_audits' by noting that sidecar proxy audits should use that instead.

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

Usage Guidelines5/5

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

Explicitly states when to use this tool (for Snowflake tag-based or column-based masking audits) and when not to (for sidecar proxy audits, use 'search_audits'). It also explains the async workflow and that all filters combine with AND logic.

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

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