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@yawlabs/aws-mcp

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by YawLabs

aws_script

Destructive

Orchestrate multiple AWS calls in a single JavaScript snippet to batch-read, filter, and aggregate data, eliminating repeated tool round-trips.

Instructions

Run a short JavaScript snippet that orchestrates other aws-mcp tools (aws.call, aws.paginate, aws.paginateAll, aws.resource.*, aws.logsTail, aws.metricsQuery, aws.iamSimulate, aws.multiRegion, aws.assumeRole, aws.docs.{search,read}) and returns a combined result. Best for batched read+filter+aggregate workflows that would otherwise need N tool round-trips: 'list all Lambdas, fetch each one's config, return those with memory > 1024'. Use return <value> at the end to surface a result; console.log lines are captured and returned alongside. Helpers throw Errors on failure -- use try/catch. NOT a security sandbox -- treat the same as any other tool the model can call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYesJavaScript snippet evaluated inside `(async () => { ... })()`. Use `return <value>` to surface a result. Bound globals: aws.call, aws.paginate, aws.paginateAll, aws.resource.{get,list,create,update,delete,status}, aws.logsTail, aws.metricsQuery, aws.iamSimulate, aws.multiRegion, aws.assumeRole, aws.docs.{search,read}, console (capture), JSON, Math, Date, Promise, Array, Object, String, Number, Boolean, Error, Intl, Atomics, SharedArrayBuffer, WebAssembly (compile blocked). Intentionally NOT bound (call as sibling MCP tools instead): aws_list_profiles, the auth/session tools, and aws_script itself. Shadowed (undefined): require, process, fetch + family, BroadcastChannel, setTimeout/Interval, queueMicrotask, Buffer, global, globalThis. NOT available (ReferenceError if used): URL, URLSearchParams, TextEncoder, TextDecoder, crypto, structuredClone, EventTarget, MessageChannel, performance, fs, import. eval/Function are disabled under Node (codeGeneration off); under the oam.js runtime they remain callable, but reach no process/require either way, so don't rely on either behavior. Tool helpers throw on failure -- wrap in try/catch when you want to handle errors per-call.
timeoutMsNoWall-clock timeout in milliseconds. Default 60000; max 300000. Best-effort across evaluation plus awaited aws.* calls -- it fires on synchronous spin before the first await and on async wall-clock once the script has yielded, but a synchronous infinite loop BETWEEN awaits can outrun the timer and is not guaranteed to be interrupted. On timeout the script stops being awaited and the tool returns an error, but any aws.* call already in flight is NOT cancelled -- it continues until its own per-call timeout (default 60s). Plan retries accordingly: a script that timed out mid 'resource.delete' may have completed the delete; re-issuing the same script can double-mutate.
Behavior5/5

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

The description goes far beyond the annotations. It discloses timeout behavior, best-effort interruption, non-cancellation of in-flight aws.* calls, risk of double-mutation on retry, console.log capture, error throwing, and sandbox limitations. This rich behavioral context complements the destructiveHint annotation with concrete risk details.

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 long but every sentence adds value. It front-loads the purpose, provides a concrete example, then systematically covers execution semantics, helpers, sandbox restrictions, and timeout behavior. No filler; dense but well-organized.

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

Completeness5/5

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

For a tool that executes arbitrary code, this is remarkably complete. It explains return values, error handling, timeouts, retry risks, and runtime limitations. Since there is no output schema, it still clarifies what the agent will receive (combined result with console.log). It fully addresses the complexity of the 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 coverage is 100%: both parameters have detailed descriptions in the schema itself, so the description doesn't need to add param-specific semantics. The tool description repeats some of the code parameter behavior but doesn't add new parameter meaning beyond the schema. Baseline 3 is appropriate when 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 runs a JavaScript snippet that orchestrates other aws-mcp tools and returns a combined result. It includes a concrete example and explicitly names the orchestratable tools, distinguishing it from sibling tools like aws_call and aws_paginate.

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

Usage Guidelines5/5

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

It explicitly says 'Best for batched read+filter+aggregate workflows that would otherwise need N tool round-trips' and provides an example. It also warns that it's not a security sandbox and lists which tools are intentionally not bound, directing the agent to call them as siblings instead. This gives clear when-to-use and when-not-to-use guidance.

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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