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ckq-aws

Resilience Architect MCP

by ckq-aws
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Python
Remote

SearchResources

Search AWS resources through Resource Explorer to locate targets for fault injection experiments by query string and view ARN.

Instructions

Search for AWS resources using Resource Explorer.

This tool searches for AWS resources using Resource Explorer based on a query string
and view ARN. It can be used to find specific resources for fault injection experiments.

Args:
    ctx: The MCP context for logging and communication
    query_string: The query string to search for resources
    view_arn: The ARN of the Resource Explorer view to use
    max_results: Maximum number of results to return (default: 100)
    next_token: Token for pagination (optional)

Returns:
    Dict containing search results and pagination information

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
view_arnYesThe ARN of the Resource Explorer view to use
next_tokenNoToken for pagination
max_resultsNoMaximum number of results to return
query_stringYesThe query string to search for resources

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses pagination behavior via next_token/max_results and a dict return, and 'search' implies a non-mutating read, but it says nothing about required permissions, query syntax limits, or result/rate constraints.

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

Conciseness3/5

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

The first two sentences are near-duplicates of each other and the Args block largely repeats the schema verbatim, adding length without new information. Front-loading of the core purpose is fine, but the redundancy costs it.

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?

With no output schema and no annotations, the description should do more. It mentions a dict of results and pagination info but not the result shape, and omits permissions, error cases, and sibling disambiguation for a four-parameter search tool.

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 each of the four parameters is already documented in the schema. The description restates them (query string, view ARN, max_results default, next_token) without adding format details, query syntax, or ARN structure beyond the schema.

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 (search) and resource (AWS resources) plus the mechanism (Resource Explorer), so the agent knows what it returns. It does not differentiate itself from siblings like ListResourceExplorerViews or DiscoverResourceRelationships, which also query Resource Explorer.

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 line 'can be used to find specific resources for fault injection experiments' gives one usage context, but there is no when-not guidance and no alternative tool named despite several Resource Explorer siblings existing. Usage is implied rather than instructed.

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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