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Compute Services List Streamlits

compute_services_list_streamlits
Read-onlyIdempotent

List Streamlit applications hosted in Snowflake, optionally filtered by pattern, database, or schema, and return quoted and qualified names for each app.

Instructions

List Streamlit applications hosted in Snowflake. Each row also has quoted_name, the name in double quotes, and, when the row has a database and schema, quoted_qualified_name.

Input Schema

NameRequiredDescriptionDefault
patternNo
databaseNoQuote names that aren't all uppercase, exactly as list tools return them.
schema_nameNoQuote names that aren't all uppercase, exactly as list tools return them.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv3.0.0
    • addedInput schema / properties / database / description
      Added value: +"Quote names that aren't all uppercase, exactly as list tools return them."
    • addedInput schema / properties / schema_name / description
      Added value: +"Quote names that aren't all uppercase, exactly as list tools return them."
  2. Addedv2.0.4

TDQS

B3/5.0
Behavior3/5

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

Annotations already declare readOnly=true, idempotent=true, destructive=false, openWorld=true, so the safety profile is covered. The description adds information about row contents (quoted_name, quoted_qualified_name), but that overlaps with the output schema rather than disclosing behavior such as filtering, pagination, or cross-database scope.

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

Conciseness4/5

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

Two sentences with the purpose front-loaded and no wasted preamble. The second sentence is a narrow implementation detail about quoted column names, which is marginal but not bloated.

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 and annotations are present, so return values and safety need not be re-explained. However, for a list tool with three optional filters, the description leaves the filtering behavior and the meaning of 'pattern' entirely unexplained, which an agent needs to call it correctly.

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 coverage is 67%: database and schema_name carry descriptions about quoting, but 'pattern' is completely undocumented in both schema and description. The description says nothing about any of the three filters, so it does not compensate for the gap on pattern.

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?

The description states a specific verb and resource: 'List Streamlit applications hosted in Snowflake.' That clearly separates it from compute_services_describe_streamlit, but it does not explicitly name the sibling or state the listing scope (account-wide vs database-scoped).

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?

There is no when-to-use guidance, no mention of when to prefer describe_streamlit over this tool, and no indication of how the optional pattern/database/schema_name filters are meant to be applied. The agent is left to infer that this lists everything unless filters are supplied.

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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