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Translate Akamai Error String

translate_error_string

Translate Akamai error reference codes into readable error details, including logs, HTTP status codes, and request/response metadata. Async operation polls until results are ready.

Instructions

Translates an Akamai error reference code (e.g. "9.6f64d440.1318965461.2f2b078") into human-readable error details including logs, HTTP status codes, and request/response metadata. This is an async operation that polls until complete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorCodeYesThe alphanumeric error reference code from Akamai error pages (e.g. "9.6f64d440.1318965461.2f2b078"). This is the "Reference #" shown on Akamai error pages.
traceForwardLogsNoWhen true, gets logs from all edge servers involved in serving the request (not just the one where the error occurred). May take longer. Defaults to false.
Behavior3/5

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

With no annotations, the description carries the full burden of disclosure. It does add a key behavioral detail: 'This is an async operation that polls until complete.' However, it doesn't mention whether this is a safe read-only operation, any authentication requirements, or potential rate limits. The async note is valuable but leaves other behavioral aspects uncovered.

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 two sentences, immediately stating the core purpose and then noting the async behavior. Every word earns its place, with no filler or repetition of schema content.

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?

The description covers the essential purpose, output scope, and async nature. Given no output schema exist, it provides a clear sense of what to expect. It doesn't detail polling mechanics or threading, but for a tool with only two parameters and a well-defined task, it is sufficiently complete.

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 already explains both parameters thoroughly. The description itself adds minimal extra parameter context beyond repeating the example code. Baseline of 3 is appropriate because the schema does the heavy lifting and the description doesn't enhance or clarify parameters further.

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 function: translating an Akamai error reference code into human-readable details. It uses a specific verb ('translates') and resource ('Akamai error reference code'), and the inclusion of example codes and output categories distinguishes it from sibling tools like translate_akamaized_url.

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

Usage Guidelines4/5

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

The description gives clear context for when to use the tool (when you have an Akamai error reference code) and implicitly distinguishes it from siblings by focusing on error codes rather than URLs or network diagnostics. However, it doesn't explicitly state when not to use it or name alternative tools for similar tasks.

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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