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Streams Read Stream Changes

streams_read_stream_changes
Read-onlyIdempotent

Query unconsumed CDC changes recorded in a Snowflake stream, returning a configurable row limit (default 10). Use it to track inserts, updates, and deletes since last consumption.

Instructions

Query unconsumed CDC changes recorded in a stream (default 10 rows).

Input Schema

NameRequiredDescriptionDefault
limitNo
stream_nameYesQuote 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. Changed1 schema field changedv3.0.0
    • addedInput schema / properties / stream_name / description
      Added value: +"Quote names that aren't all uppercase, exactly as list tools return them."
  2. Addedv2.0.4

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true and destructiveHint=false, so the safety profile is covered. The description adds the default row cap, which is useful. However, the single most important behavior for a CDC stream reader — whether and when reading marks changes as consumed (transaction/commit semantics) — is left entirely implicit, which is a meaningful omission for a tool whose whole purpose is consuming change rows.

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 filler; the resource and the default row count both arrive before any qualifier. Nothing in it is redundant to the point of waste.

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 described, and the annotations carry the read-only/idempotency story. What is missing is the consumption model — whether rows are re-readable, whether a transaction must commit for changes to be consumed, and how this pairs with streams_describe_stream — which matters for correctly sequencing calls.

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

Parameters3/5

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

Schema coverage is 50%: stream_name is documented in the schema, but limit is not, so the description's '(default 10 rows)' partially compensates for that gap. It still doesn't say whether limit is a hard cap, a maximum the server honors, or whether it can be raised, so the compensation is incomplete.

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?

States a specific verb (query) and a specific resource (unconsumed CDC changes in a stream), and names the default row cap, so an agent knows this reads change data rather than metadata. It is distinguishable from streams_describe_stream and streams_list_streams by the word 'changes', though it never names those siblings to reinforce the contrast.

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 explicit statement of when to call this versus streams_describe_stream or streams_list_streams, and no preconditions (privileges, whether a stream must be created first). The word 'unconsumed' implies the use case but the agent must infer it.

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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