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hey-iam-ryan

aws-knowledge-plus

by hey-iam-ryan

read_aws_content

Fetch a supported AWS knowledge page and return it as clean markdown. Re:Post questions, answers, and kiro.dev docs are converted with authors, dates, and vote counts; long pages include a resume marker.

Instructions

Fetch a page from a supported source and return it as markdown.

Dispatches on the URL's host:

  • repost.aws/questions/<id> — the question plus every answer, rebuilt from the page's schema.org QAPage data with authors, dates and vote counts.

  • kiro.dev/docs/... — the published markdown twin of the page, so the text arrives without site chrome. Blog and changelog pages are converted from HTML.

  • builder.aws.com/content/... — feed summary only; the body is client-rendered and is not retrieved.

Long pages are truncated with an explicit marker telling you the start_index to resume from.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesURL returned by search_aws_knowledge.
max_lengthNoMaximum characters to return.
start_indexNoCharacter offset, for continuing a long read.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations available, the description carries the full burden of behavioral disclosure and does so thoroughly. It explains host-dependent behavior, which sources return raw markdown versus HTML conversion, that builder.aws.com bodies are excluded, and that long pages are truncated with a start_index marker for resumption.

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 compact, front-loads the core action, and uses a scannable bullet list for the host-specific dispatch behavior. Every sentence contributes useful information and none are wasted on filler.

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 with three parameters, a clear output schema, and no annotations, the description is complete enough for an agent to invoke correctly. It covers all important call-time behaviors: supported host patterns, content transformation, truncation, and continuation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the parameters are already well documented. The description adds meaningful context by relating max_length and start_index to the truncation behavior and the resume marker, going slightly beyond the schema without restating it.

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 opens with a specific verb and resource: "Fetch a page from a supported source and return it as markdown." It then confirms differentiation with concrete host-specific behaviors, so an agent can distinguish it from search_aws_knowledge and list_sources without guessing.

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 when to use the tool—when you already have a URL from a supported source—and the schema documents that the URL comes from search_aws_knowledge. However, it never explicitly states the workflow relationship to its siblings or says when not to use it, leaving some routing to inference.

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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