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d3p_error-translator

Translates HTTP status codes into human-readable explanations with fix suggestions.

Instructions

Translate HTTP status codes into human-readable explanations with fix suggestions. Category: data | Cost: 3 sats | Endpoint: error-translator Parameters (pass as JSON string): status_code (integer) (required): HTTP status code to translate

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsNo{}

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the core function and adds cost/endpoint info, but does not explain side effects, authentication needs, rate limits, or whether the operation is read-only or destructive. Behavioral transparency is minimal.

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 extremely concise: one sentence for purpose, one line for metadata, and one line for the parameter. Every sentence adds value without redundancy. It is front-loaded with the essential action.

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?

The tool is simple with one parameter, but the description does not address what happens with invalid status codes, how 'fix suggestions' are structured, or how to interpret the output (though an output schema exists). The inconsistency with the required parameter also undermines completeness. Adequate but leaves gaps.

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?

The input schema only specifies a 'params' string with no description (0% coverage). The description adds meaning by explaining that the JSON string should contain a required 'status_code' integer. However, it contradicts the schema which has no required fields, and does not clarify if other properties are possible. Partial compensation with an inconsistency.

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 a specific verb ('Translate') and resource ('HTTP status codes'), including the output ('human-readable explanations with fix suggestions'). It is distinct from sibling tools which cover different domains like search, pricing, or validation.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives, when not to use it, or specific prerequisites. The mention of 'Category: data' is too vague to provide actionable usage direction, and no exclusions or use cases are given.

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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