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aws_dynamodb_query

Query AWS DynamoDB tables using key condition expressions to retrieve items as JSON objects, with support for filters, indexes, and sorting.

Instructions

Query a DynamoDB table using a key condition expression. Items are returned deserialized as plain JSON objects.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
profileNoAWS profile name from ~/.aws/config (e.g., 'default', 'production')
regionNoAWS region override (e.g., 'us-east-1', 'sa-east-1')
table_nameYesDynamoDB table name
key_condition_expressionYesKey condition (e.g., 'pk = :pkval AND begins_with(sk, :skprefix)')
expression_attribute_valuesYesValues for expression placeholders in DynamoDB format (e.g., {":pkval": {"S": "user#123"}})
expression_attribute_namesNoName placeholders for reserved words (e.g., {"#s": "status"})
filter_expressionNoAdditional filter applied after the query
index_nameNoName of a GSI or LSI to query
limitNoMaximum items to evaluate
scan_index_forwardNoTrue for ascending order, False for descending (default: True)
Behavior3/5

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

Adds valuable output transformation detail ('deserialized as plain JSON objects') absent from annotations, indicating DynamoDB typed JSON is converted to plain objects. However, misses critical DynamoDB behaviors: pagination/LastEvaluatedKey, 1MB result limits, consumed capacity, and eventually consistent reads vs strong consistency options.

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?

Two well-structured sentences with zero waste. First sentence establishes operation and mechanism; second sentence discloses output format. Information density is high with no filler or redundancy.

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?

Adequate for basic operation given 100% schema coverage, but gaps remain for a complex 10-parameter query tool without output schema: missing pagination behavior, filter expression application timing (post-query), and index usage details. Sufficient to invoke but not to handle result sets optimally.

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 100% with detailed parameter descriptions including examples. Description references 'key condition expression' reinforcing the main parameter purpose, but does not add semantic details beyond what schema already provides. Baseline 3 appropriate for high-coverage schemas.

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?

Specific verb 'Query' + resource 'DynamoDB table' + mechanism 'key condition expression' clearly identifies the operation. Implicitly distinguishes from sibling aws_dynamodb_scan by emphasizing key conditions (vs full scan) and from describe_table by focusing on data retrieval vs metadata.

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

Usage Guidelines3/5

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

Implies usage scenario through 'key condition expression' (suggests use when partition key is known), but lacks explicit when-to-use guidance comparing to aws_dynamodb_scan or stating requirements like mandatory partition key conditions. No explicit alternatives named.

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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