Skip to main content
Glama
senoff

xlsx-for-ai

xlsx_slicers_timelines

Read-onlyIdempotent

Extract all slicer and timeline metadata from a local .xlsx file. Use to document dashboard filter UI for AI agents or audit slicer bindings after data changes.

Instructions

List every slicer (interactive filter button) and timeline (date-range filter visual) in a LOCAL .xlsx file with their captions, source bindings (table column or pivot table), and timeline granularity (years / quarters / months / days) plus the currently-selected date range.

Reads the OOXML zip (xl/slicers/, xl/slicerCaches/, xl/timelines/, xl/timelineCaches/) directly — a surface ExcelJS silently drops on round-trip.

USE WHEN: documenting a dashboard so an LLM knows what filter UI a human sees. Or auditing whether a slicer's binding still matches the underlying data after a refactor.

DO NOT USE WHEN: just reading values (use xlsx_read). Or trying to APPLY a filter (use xlsx_filter — slicers/timelines are UI metadata, not data filters).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_b64Yes
Behavior4/5

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

Beyond annotations (readOnlyHint, etc.), the description discloses that it reads OOXML zip directly and that ExcelJS drops these on round-trip, adding valuable behavioral context.

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, well-organized with clear sections, and every sentence adds value without redundancy.

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?

For a list-type tool with no output schema, the description fully specifies what is listed and how it works, including internal paths, providing complete context.

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 coverage is 0% for the single parameter file_b64. The description implies the file is a base64-encoded local .xlsx file but does not explicitly describe the parameter, leaving some ambiguity.

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 precisely states the tool lists slicers and timelines in an .xlsx file, specifying details like captions, source bindings, and timeline granularity. It distinguishes from siblings like xlsx_read and xlsx_filter.

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 guidance on appropriate contexts and alternatives, such as using xlsx_read for values and xlsx_filter for applying filters.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/senoff/xlsx-for-ai'

If you have feedback or need assistance with the MCP directory API, please join our Discord server