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doc2x_materialize_convert_zip

Extract and write ZIP files from base64 data to a specified directory, using system unzip when available or writing the file directly.

Instructions

Materialize convert_zip (base64) into output_dir. Best-effort: tries system unzip first; otherwise writes the zip file.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
convert_zip_base64Yes
output_dirYes
Behavior3/5

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 reveals the tool's 'best-effort' nature and two-step process (system unzip first, then write zip file), which adds useful context beyond the basic operation. However, it doesn't cover critical aspects like error handling, permissions needed for output_dir, or what 'materialize' entails in terms of file structure or overwrites.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized with two concise sentences. The first sentence front-loads the core purpose, and the second adds behavioral context without redundancy. Every sentence earns its place by clarifying the operation and fallback mechanism, though it could be slightly more structured (e.g., bullet points for steps).

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

Completeness2/5

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

Given the complexity of handling zip files and base64 encoding, with no annotations and no output schema, the description is incomplete. It misses key details: what 'materialize' means (extract? copy?), error responses, output format, or success indicators. For a tool with 2 parameters and significant behavioral nuance, this leaves the agent under-informed about execution and outcomes.

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 0%, so the description must compensate. It explains that convert_zip_base64 is a base64-encoded zip file to materialize and output_dir is the target directory, adding meaning beyond the schema's minimal type constraints. However, it doesn't detail format expectations (e.g., zip structure, encoding standards) or directory requirements (e.g., must exist), leaving gaps in parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: materializing a base64-encoded zip file into an output directory. It specifies the verb 'materialize' and the resource 'convert_zip (base64)', which distinguishes it from sibling tools focused on conversion, parsing, or downloading. However, it doesn't explicitly differentiate from all siblings (e.g., doc2x_download_url_to_file might also handle files), so it's not a perfect 5.

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?

The description provides no guidance on when to use this tool versus alternatives. It mentions a 'best-effort' approach with system unzip as a fallback, but doesn't specify prerequisites, error conditions, or comparisons to sibling tools like doc2x_convert_export_result. Without explicit when/when-not instructions, the agent lacks context for proper selection.

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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