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senoff

xlsx-for-ai

xlsx_hyperlinks

Read-onlyIdempotent

Extract and classify every hyperlink in an Excel workbook—shows anchor cell, URL, display text, tooltip, and kind (external, internal, mailto). Use for security audits or URL reference lists.

Instructions

list every hyperlink in a workbook with its anchor cell, target URL/anchor, display text, tooltip, and a kind classifier (external / internal / mailto / unknown). No other tool can do this: pandas drops hyperlinks on read entirely; openpyxl gives raw access but does not classify or aggregate; this surfaces all links plus a per-kind tally for instant audit.

USE WHEN: security-auditing a workbook before opening it (what URLs does it point at?). Or extracting a reference list of URLs from a financial model / dashboard. Or finding mailto links for a contact-list workbook. Free tier — counts against the 10k/mo cap.

DO NOT USE WHEN: trying to follow / fetch the targets (this tool does not fetch — by design, for safety). Or just reading cell text (use xlsx_read).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_b64Yes
optionsNo
Behavior5/5

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

Annotations already mark it readOnly, destructiveHint false, idempotent. Description adds 'does not fetch — by design, for safety', confirming it's a pure read operation. No contradiction.

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 moderately long but well-structured: purpose sentence, competitive advantage, use cases, and exclusions. Every sentence adds value, though the 'Free tier' note could be integrated more concisely.

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?

Given 2 params (1 required), no output schema, but rich annotations, the description is fairly complete: it explains output fields, use cases, and limitations. Missing detail on file_b64 encoding and output format, but acceptable for a simple 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?

Schema coverage is 0% (no parameter descriptions in schema). Description does not explain the input parameters (file_b64, options with limit and sheet) beyond implying a workbook input. This is insufficient compensation for the lack of schema documentation.

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 lists hyperlinks with specific fields (anchor cell, target URL, display text, tooltip, kind classifier). It distinguishes from siblings by noting pandas drops hyperlinks and openpyxl doesn't classify/aggregate, making the purpose specific and differentiated.

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?

Explicit USE WHEN and DO NOT USE WHEN sections provide clear context: security auditing, URL extraction, not for fetching targets or reading cell text (redirects to xlsx_read). Also mentions free tier cap.

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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