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senoff

xlsx-for-ai

xlsx_properties

Read-onlyIdempotent

Extract all metadata properties from a local .xlsx file including creator, timestamps, custom fields, and more. Use to audit workbook attribution or remove sensitive info before sharing.

Instructions

Surface the workbook's identity card from a LOCAL .xlsx file. Core: creator, last_modified_by, created/modified/lastPrinted timestamps, title, subject, company, manager, keywords, category, description. Application: app name + version, doc security label, hyperlink base. Custom: every user-defined Info > Properties entry (Department, ReviewedBy, ApprovalRequired, etc.) with type tag and value.

Reads docProps/core.xml, docProps/app.xml, and docProps/custom.xml directly — a surface pandas drops entirely.

USE WHEN: auditing a workbook for attribution ("who built this and when?"). Or stripping sensitive metadata before sharing externally. Or extracting custom finance/legal flags ("ReviewedBy", "ApprovalRequired") that workflows pin to the file.

DO NOT USE WHEN: just reading values (use xlsx_read). Or trying to MODIFY metadata (use xlsx_redact for sensitive-field stripping).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_b64Yes
Behavior5/5

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

Annotations already declare readOnlyHint, destructiveHint, idempotentHint, and openWorldHint. The description adds valuable context: the tool reads specific XML files (docProps/core.xml, app.xml, custom.xml) and does not modify data, confirming its read-only nature.

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 well-organized with clear sections and usage guidance. Some redundancy exists (e.g., repeating 'core' vs specific fields), but overall it is concise and front-loaded.

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 parameter and no output schema, the description fully covers purpose, usage, behavioral context, and alternatives. It is self-contained and sufficient for an agent to correctly invoke the tool.

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

Parameters2/5

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

The single parameter file_b64 has no schema description (0% coverage). The description only mentions 'from a LOCAL .xlsx file' but does not explain that the parameter is a base64-encoded string, which is critical for correct usage.

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: to surface the workbook's identity card from a local .xlsx file, listing specific properties and sources. It distinguishes from siblings like xlsx_read and xlsx_redact by specifying when not to use them.

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

Usage Guidelines5/5

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

Explicitly states when to use (auditing, stripping metadata, extracting custom flags) and when not to use (just reading values, modifying metadata), with clear sibling alternatives (xlsx_read, xlsx_redact).

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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