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get_error_doc

Fetch structured error documentation for any error code, including cause, fix, examples, and related errors. Resolve issues quickly with clear guidance.

Instructions

Fetch the structured error documentation for a given error code.

    ``what`` and ``why`` come from the in-memory registry
    (``echolon.errors.ERROR_CATALOG``); the long-form sections (``fix``,
    ``example``, ``common_causes``, ``related``) come from the per-code
    markdown at ``echolon/native/errors/codes/{code}.md``. The full
    markdown body is also returned as ``long_form_markdown`` so an
    agent can consume the prose verbatim if the parsed sections are
    empty (parser-resilience fallback).

    Args:
        code: Error code like 'VAL-001' or 'IND-003'.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYes
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the dual data sources (in-memory registry and markdown files) and the parser-resilience fallback behavior. However, it does not mention authentication requirements, rate limits, or other potential behavioral traits.

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 concise yet informative, with clear structure (overview, internal details, fallback). It front-loads the purpose and uses bullet points, making it easy to scan. Every sentence adds value.

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?

Given the simple tool (1 parameter, no output schema, no annotations), the description is remarkably complete. It explains the two-part data source, the fields returned (what, why, fix, etc.), and the fallback mechanism. No major gaps remain.

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?

The only parameter 'code' has 0% schema description coverage. The description adds meaning by providing examples ('VAL-001', 'IND-003') and explaining it represents an error code. This compensates for the schema's lack of detail, but no full pattern or constraints are given.

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 'Fetch the structured error documentation for a given error code', specifying both the action (fetch) and the resource (error documentation). It implicitly distinguishes from siblings like get_doc or get_pattern by focusing specifically on error codes.

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 is provided on when to use this tool versus alternatives (e.g., get_doc for general documentation). There is no mention of prerequisites, contexts, or when not to use it.

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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