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localstack

LocalStack MCP Server

Official
by localstack

localstack-chaos-injector

Destructive

Inject and manage chaos faults and network latency in LocalStack to test AWS service resilience during development.

Instructions

Injects, manages, and clears chaos faults and network effects in LocalStack to test system resilience.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesThe specific chaos engineering action to perform.
rulesNoAn array of fault rules. Required for 'inject-faults', 'add-fault-rule', and 'remove-fault-rule' actions.
latency_msNoNetwork latency in milliseconds. Required for the 'inject-latency' action.
Behavior4/5

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

Annotations already indicate destructiveHint=true (mutation), readOnlyHint=false, and idempotentHint=false, but the description adds valuable context: it clarifies that the tool handles both 'chaos faults' and 'network effects' (e.g., latency), which helps the agent understand the scope beyond just faults. However, it doesn't detail rate limits, auth needs, or specific destructive outcomes like data loss.

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, efficient sentence that front-loads key actions ('injects, manages, and clears') and the purpose ('to test system resilience'). Every word earns its place without redundancy or fluff, making it easy for an agent to parse quickly.

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

Completeness4/5

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

Given the tool's complexity with 3 parameters, 100% schema coverage, and no output schema, the description is reasonably complete: it covers the tool's domain (chaos engineering) and key actions. However, it could improve by hinting at output behavior (e.g., what 'get-faults' returns) or error handling, as annotations only cover basic hints.

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 schema fully documents parameters like 'action' with enum values and 'rules' with nested properties. The description adds no additional parameter semantics beyond implying chaos-related inputs, meeting the baseline of 3 since the schema does the heavy lifting.

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?

The description clearly states the tool's purpose with specific verbs ('injects, manages, and clears') and resources ('chaos faults and network effects in LocalStack'), plus the goal ('to test system resilience'). It distinguishes itself from sibling tools like logs-analysis or deployer by focusing on chaos engineering rather than deployment, logging, or client operations.

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?

The description implies usage for testing resilience in LocalStack, but it doesn't explicitly state when to use this tool versus alternatives like the 'localstack-aws-client' for normal operations or 'localstack-logs-analysis' for post-failure analysis. No exclusions or prerequisites are mentioned, leaving the agent to infer context from the chaos engineering domain.

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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