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Bilig WorkPaper

by io.github.proompteng

Read WorkPaper Range

read_range
Read-onlyIdempotent

Read calculated values plus serialized formulas/inputs for an A1 range. Use for audit readback after edits; use read_cell for one address.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rangeYesA1 range such as Summary!A1:B5. If omitted from the range, pass sheetName separately.
sheetNameNoDefault sheet name when range omits a sheet name, for example Summary.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rangeYesCanonical A1 range including the sheet name.
valuesYesTwo-dimensional array of evaluated cell values.
serializedYesTwo-dimensional array of raw serialized cell contents, including formulas.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds valuable context that the tool returns calculated values plus serialized formulas/inputs, revealing the output composition beyond a simple read, and its intended audit role. This exceeds annotation-only information without contradicting it.

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 a concise two-sentence structure: the first sentence states core functionality, the second provides usage context and alternative guidance. Every sentence earns its place with zero 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?

Given the tool's low complexity (2 params, output schema present) and strong annotations, the description covers the what, when, why, and alternative. It also clarifies the output involves formulas/inputs and audit usage, making it complete for an agent to select and invoke correctly.

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 100% for both parameters, with descriptions for 'range' and 'sheetName'. The tool description does not add new details about parameter syntax or behavior beyond the schema, so the baseline of 3 is appropriate.

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 reads calculated values plus serialized formulas/inputs for an A1 range, using a specific verb and resource. It explicitly distinguishes itself from the sibling read_cell tool by noting the latter is for a single address, leaving no ambiguity about scope.

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?

It provides an explicit use case ('audit readback after edits') and directs users to the alternative read_cell for one-address reads. This gives clear guidance on when to use this tool versus its sibling, which is exemplary.

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

All Bilig WorkPaper toolsInspect
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TDQS

A4.3/5.0
Disambiguation4/5

Tools are mostly distinct with clear purposes for reading, writing, exporting, and validating. Slight overlap exists between get_cell_display_value and read_cell, and between the two set_cell variants, but descriptions clarify the intended use.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern (e.g., list_sheets, read_cell, validate_formula). This predictable naming makes the set easy to navigate.

Tool Count5/5

With 8 tools, the set is well-scoped for interacting with a WorkPaper document. Each tool serves a clear purpose without unnecessary bloat.

Completeness3/5

Core operations for reading, writing, validating, and exporting are covered, but the surface lacks batch cell writes, cell clearing, and sheet management. These notable gaps may hinder complex editing workflows.

Resources