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ddb_optimize_queries

Optimize DynamoDB queries by analyzing access patterns and read capacity to reduce costs and improve performance.

Instructions

Analyze and optimize DynamoDB query patterns for performance and cost (Pro)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyNoAPI key for authentication
table_nameYesDynamoDB table name
current_rcuNoCurrent read capacity units consumed
access_patternsYesList of access patterns to optimize
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure, but it only says 'Analyze and optimize' without revealing whether this tool makes changes to DynamoDB, returns recommendations, is read-only, or requires specific IAM permissions. The '(Pro)' marker hints at a paid feature but does not clarify behavior.

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 a single front-loaded sentence with no filler. Every phrase contributes: the action, the target resource, the optimization goals, and the plan qualifier.

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

Completeness2/5

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

This is a DynamoDB query-optimization tool with no output schema and no annotations, yet the description omits key context such as what the tool returns, whether it mutates infrastructure, how it handles the current_rcu and access_patterns inputs, and when to use it instead of the many related sibling tools. The one-line description is under-specified for safe invocation.

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 description coverage is 100%, so the baseline is 3. The description adds no extra meaning to the parameters, such as the expected format for access_patterns or how current_rcu is used, but it does not need to because the schema already documents all four parameters.

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 clear verb ('Analyze and optimize') and a specific resource ('DynamoDB query patterns') with an explicit goal ('performance and cost'). It is distinguishable from non-DynamoDB optimization siblings, but it does not explicitly distinguish itself from related DynamoDB table/GSI tools like ddb_design_table or ddb_generate_gsi.

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?

No guidance is given about when to use this tool versus alternative DynamoDB or query-optimization siblings. There is no mention of prerequisites, exclusions, or routing criteria such as 'use ddb_generate_gsi when you need secondary indexes'.

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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