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Snowflake List Secrets

snowflake_list_secrets
Read-only

List API keys, OAuth credentials, and other security secrets stored in Snowflake. Filter by pattern, database, or schema.

Instructions

List security secrets (API keys, OAuth credentials) stored in Snowflake.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
patternNo
databaseNo
schema_nameNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed6 schema fields changedv1.2.0
    • addedInput schema / additionalProperties
      Added value: +false
    • removedInput schema / properties / database / title
      Removed value: -"Database"
    • removedInput schema / properties / pattern / title
      Removed value: -"Pattern"
    • removedInput schema / properties / schema_name / title
      Removed value: -"Schema Name"
    • removedInput schema / title
      Removed value: -"snowflake_list_secretsArguments"
    • removedOutput schema / title
      Removed value: -"snowflake_list_secretsDictOutput"
  2. First observedv0.1.0

TDQS

B3.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true and destructiveHint=false, so the safety profile is covered. The description adds only the content of what is listed (API keys, OAuth credentials), but says nothing about required privileges for reading secrets, whether values are masked, or scoping behavior. With annotations carrying the safety load, this is an adequate-but-thin 3.

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?

A single front-loaded sentence with zero padding. The core verb+resource leads and the parenthetical examples are earned, not filler.

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

Completeness3/5

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

An output schema exists so return values need not be explained, and the read-only annotations cover safety. However, three entirely undocumented parameters and the absence of any filtering/scoping guidance leave the definition only minimally viable for correct invocation.

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

Parameters2/5

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

Schema description coverage is 0% — pattern, database and schema_name have no descriptions anywhere. The description does not compensate at all: it never explains that pattern is a name filter, that database/schema_name scope the listing, or whether the filter is a LIKE/wildcard pattern. This is a real gap for a 3-param tool.

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

Purpose4/5

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

Specific verb+resource ("List security secrets") with clarifying examples of the resource type (API keys, OAuth credentials). An agent knows exactly what domain this covers. It does not explicitly contrast with the sibling snowflake_describe_secret, so it stops short of a 5.

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

Usage Guidelines2/5

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

The description offers no when-to-use guidance, no prerequisites, and never names the obvious alternative (snowflake_describe_secret) for drilling into a single secret. The agent must infer usage purely from the tool name.

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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