LibreOffice MCP Server
Provides tools for creating, reading, converting, editing, and analyzing LibreOffice documents, including Writer, Calc, Impress, and Draw files, spreadsheet data, batch conversion, merging, document search, statistics, and live viewing/editing through a LibreOffice extension.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@LibreOffice MCP Serverconvert report.docx to PDF, keeping the formulas rendered"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
mcp-libre(工作增强版)
Fork 自 patrup/mcp-libre(MIT),感谢原作基座。本版在其上增强:
公式感知路由:docx 含 OMML 公式时自动改走 Word COM 真渲染(LibreOffice 会忽略公式字号,Bug 32419)
Word COM 优先:Windows 上 docx→pdf 默认先走 Word(大带图文档 LO 常超时,Word 快 5 倍+字体保真),失败自动回退 LO
MCP 形态接入:任意 MCP 客户端可注册(uv venv + 依赖安装后以 stdio 运行 src/main.py)
安装:git clone 本仓库 → uv venv .venv && uv pip install -r requirements(或参考 pyproject.toml)→ MCP 客户端注册 command: <仓库>/.venv/Scripts/python.exe, args: [<仓库>/src/main.py]。
LibreOffice MCP Server
A comprehensive Model Context Protocol (MCP) server that provides tools and resources for interacting with LibreOffice documents. This server enables AI assistants and other MCP clients to create, read, convert, and manipulate LibreOffice documents programmatically.
📂 Repository Structure
This repository is organized into logical directories:
src/- Core MCP server implementationtests/- Test suite and validation scriptsexamples/- Demo scripts and usage examplesconfig/- Configuration templates for integrationsscripts/- Utility scripts for setup and managementdocs/- Comprehensive documentation
For detailed information, see docs/REPOSITORY_STRUCTURE.md.
Related MCP server: MCP Documents
🚀 Features
LibreOffice Extension (Plugin) - NEW! 🎉
Native Integration: Embedded MCP server directly in LibreOffice
Real-time Editing: Live document manipulation with instant visual feedback
Performance: 10x faster than external server (direct UNO API access)
Multi-document: Work with all open LibreOffice documents
Auto-start: Automatically available when LibreOffice starts
HTTP API: External AI assistant access via localhost:8765
Document Operations
Create Documents: New Writer, Calc, Impress, and Draw documents
Read Content: Extract text from any LibreOffice document
Convert Formats: Convert between 50+ formats (PDF, DOCX, HTML, etc.)
Edit Documents: Insert, append, or replace text in Writer documents
Document Info: Get detailed metadata about documents
Spreadsheet Operations
Read Spreadsheets: Extract data from Calc spreadsheets and Excel files
Structured Data: Get data as 2D arrays with row/column information
Advanced Tools
Document Search: Find documents containing specific text
Batch Convert: Convert multiple documents simultaneously
Merge Documents: Combine multiple documents into one
Document Analysis: Get detailed statistics (word count, sentences, etc.)
Live Viewing & Real-time Editing
GUI Integration: Open documents in LibreOffice for live viewing
Real-time Updates: See changes as AI assistants modify documents
Change Monitoring: Watch documents for modifications in real-time
Interactive Sessions: Create live editing sessions with automatic refresh
MCP Resources
Document Discovery: List all LibreOffice documents (
documents://)Content Access: Access specific document content (
document://{path})
📋 Requirements
LibreOffice: 24.2+ (must be accessible via command line)
Python: 3.12+
UV Package Manager: For dependency management
For detailed installation instructions for all platforms, run:
./mcp-helper.sh requirements🛠 Installation
Clone the repository:
git clone https://github.com/patrup/mcp-libre/ cd mcp-libreCheck prerequisites:
./mcp-helper.sh requirements # Show detailed requirements ./mcp-helper.sh check # Verify your systemInstall dependencies:
uv syncMake helper script executable:
chmod +x mcp-helper.sh
🎯 Quick Start
Test the Server
# Run functionality tests
./mcp-helper.sh test
# Run interactive demo
./mcp-helper.sh demoStart MCP Server
# Standard MCP mode (stdio)
python src/main.py
# Or using UV
uv run python src/main.py
# Show help and options
python src/main.py --help
# Run tests
python src/main.py --testIntegration with Super Assistant
# Start the MCP proxy
./mcp-helper.sh proxy
# Then configure Super Assistant extension:
# Server URL: http://localhost:3006🔧 Available Tools
Tool | Description |
| Create new LibreOffice documents |
| Extract text from documents |
| Convert between formats |
| Get document metadata |
| Read spreadsheet data |
| Edit document text |
| Search documents by content |
| Batch format conversion |
| Merge multiple documents |
| Document analysis |
| Open document in GUI for live viewing |
| Start live editing with real-time preview |
| Monitor document changes in real-time |
| Force document refresh in GUI |
📚 Documentation
Prerequisites: Quick reference for system requirements
Plugin Migration Guide: Migrate from external server to plugin
Examples: Code examples and usage patterns
Live Viewing Guide: See changes live in LibreOffice GUI
Super Assistant Setup: Chrome extension integration
ChatGPT Browser Guide: Using with ChatGPT and alternatives
Troubleshooting: Common issues and solutions
Quick Start: Quick reference guide
Complete Solution: Comprehensive overview
🔗 Integration Options
1. LibreOffice Extension (NEW - Recommended!) 🎉
The most powerful and efficient way to use the MCP server:
# Build and install the LibreOffice extension
cd plugin/
./install.sh install
# Test the extension
./install.sh testBenefits of the Extension:
10x Performance: Direct UNO API access (no subprocess overhead)
Real-time Editing: Live document manipulation in open LibreOffice windows
Native Integration: Appears in LibreOffice Tools menu
Multi-document Support: Work with all open documents simultaneously
Auto-start: Automatically starts with LibreOffice
Advanced Features: Full access to LibreOffice formatting and capabilities
Usage:
The extension provides an HTTP API on
http://localhost:8765Configure your AI assistant to use this endpoint
Access controls via Tools > MCP Server in LibreOffice
Real-time document editing with instant visual feedback
For detailed plugin information, see plugin/README.md.
2. Claude Desktop
Generate configuration automatically:
./generate-config.sh claude
# Creates ~/.config/claude/claude_desktop_config.jsonThen restart Claude Desktop and start using LibreOffice commands:
"Create a new Writer document and save it as project-report.odt"
"Convert my document to PDF format"
3. Super Assistant Chrome Extension
Generate configuration and start proxy:
./generate-config.sh mcp
npx @srbhptl39/mcp-superassistant-proxy@latest --config ~/Documents/mcp/mcp.config.json
# Server URL: http://localhost:30064. Direct MCP Client
from mcp.shared.memory import create_connected_server_and_client_session
from libremcp import mcp
async with client_session(mcp._mcp_server) as client:
result = await client.call_tool("create_document", {
"path": "/tmp/test.odt",
"doc_type": "writer",
"content": "Hello, World!"
})🎨 Usage Examples
Natural Language (via Super Assistant)
"Create a new Writer document with a project report"
"Convert my ODT file to PDF format"
"Search for documents containing 'budget' in my Documents folder"
"Get statistics for my essay - how many words?"
Programmatic Usage
from libremcp import create_document, read_document_text, convert_document
# Create a document
doc = create_document("/tmp/report.odt", "writer", "Project Report")
# Read content
content = read_document_text("/tmp/report.odt")
print(f"Words: {content.word_count}")
# Convert to PDF
result = convert_document("/tmp/report.odt", "/tmp/report.pdf", "pdf")📁 Supported File Formats
Input (Reading)
LibreOffice:
.odt,.ods,.odp,.odgMicrosoft Office:
.doc,.docx,.xls,.xlsx,.ppt,.pptxText:
.txt,.rtf
Output (Conversion)
PDF:
.pdfMicrosoft Office:
.docx,.xlsx,.pptxWeb:
.html,.htmText:
.txtLibreOffice:
.odt,.ods,.odp,.odgMany others: 50+ formats supported by LibreOffice
🧪 Testing
LibreOffice Extension Testing
# Install and test the plugin
cd plugin/
./install.sh install # Build and install extension
./install.sh test # Test functionality
./install.sh status # Check status
./install.sh interactive # Interactive testing modeExternal Server Testing
# Show system requirements and installation guides
./mcp-helper.sh requirements
# Check dependencies and verify setup
./mcp-helper.sh check
# Run built-in functionality tests
./mcp-helper.sh test
# Interactive demo of all capabilities
./mcp-helper.sh demo
# Test specific functionality directly
uv run python libremcp.py --test🔧 Configuration
MCP Configuration for Integrations
Generate personalized configuration files for Claude Desktop and/or Super Assistant:
# Generate both Claude Desktop and Super Assistant configs
./generate-config.sh
# Generate only Claude Desktop config
./generate-config.sh claude
# Generate only Super Assistant config
./generate-config.sh mcp
# Generate Super Assistant config in custom location
./generate-config.sh mcp /path/to/custom/directoryThis automatically creates configurations with your actual project paths:
Claude Desktop:
~/.config/claude/claude_desktop_config.jsonSuper Assistant:
~/Documents/mcp/mcp.config.json(or custom location)
Environment Variables
export PYTHONPATH="/path/to/mcp-libre"
export LIBREOFFICE_PATH="/usr/bin/libreoffice" # OptionalCustom Search Paths
Edit libremcp.py to modify document discovery locations:
search_paths = [
Path.home() / "Documents",
Path.home() / "Desktop",
Path("/custom/path"),
Path.cwd()
]🛡 Security
Local Execution: All operations run locally
File Permissions: Limited to user's file access
No Network: No external network dependencies
Temporary Files: Automatically cleaned up
🚨 Troubleshooting
LibreOffice Issues
# Check LibreOffice installation
libreoffice --version
libreoffice --headless --help
# Test conversion manually
libreoffice --headless --convert-to pdf document.odtJava Warnings
Java warnings are usually non-fatal
Core functionality works without Java
Install Java for full LibreOffice features
Permission Errors
Check file and directory permissions
Ensure LibreOffice can access document paths
Verify write permissions for output directories
🤝 Contributing
Fork the repository
Create a feature branch
Make your changes
Add tests if applicable
Submit a pull request
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
The MIT License is a permissive license that allows:
✅ Commercial use
✅ Modification
✅ Distribution
✅ Private use
For other license options, see LICENSE_OPTIONS.md.
🔗 Links
MCP Specification: https://spec.modelcontextprotocol.io/
LibreOffice: https://www.libreoffice.org/
FastMCP Framework: https://github.com/modelcontextprotocol/python-sdk
📞 Support
Issues: Use GitHub issues for bug reports
Documentation: See the
docs/folder for detailed guidesExamples: Check
EXAMPLES.mdfor usage patterns
LibreOffice MCP Server v0.1.0 - Bridging AI and Document Processing
Available Tools
15 toolsbatch_convert_documentsC
Convert multiple documents in a directory to a different format
Args:
source_dir: Directory containing source documents
target_dir: Directory where converted documents should be saved
target_format: Target format for conversion
source_extensions: List of source file extensions to convert (default: common formats)
| Name | Required | Description | Default |
|---|---|---|---|
| source_dir | Yes | ||
| target_dir | Yes | ||
| target_format | Yes | ||
| source_extensions | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, and it discloses almost nothing beyond the basic action: it doesn't say whether subdirectories are traversed, whether existing files in target_dir are overwritten, whether source files are left untouched, what happens if target_dir is missing, or how failures in a batch are reported. For a bulk write operation this is a significant transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with a one-line summary followed by a compact Args block, with no redundant prose. The docstring formatting is slightly mechanical but nothing is wasted.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return-value explanation isn't required, but for a batch mutation tool with zero annotations and four parameters the description should at least cover overwrite behavior, recursion, and error handling. As written it is adequate to invoke the tool but leaves consequential side effects undocumented.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the Args block does real work by mapping each parameter to its role and noting that source_extensions defaults to 'common formats'. However, the explanations largely restate the parameter names — target_format's accepted values (e.g. 'pdf', 'docx') and source_extensions' expected syntax are never specified.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The first line gives a specific verb and resource ('Convert multiple documents') plus the batch scope ('in a directory') and the outcome ('to a different format'), which clearly separates it from siblings like read_document_text or merge_text_documents. It stops short of naming a sibling it is distinct from, so it isn't a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to choose this over single-document conversion, read_document_text, or search_documents, and no prerequisites (e.g. whether LibreOffice must be running). The reader must infer usage entirely from the tool name and directory-based framing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
create_documentB
Create a new LibreOffice document
Args:
path: Full path where the document should be created
doc_type: Type of document to create (writer, calc, impress, draw)
content: Initial content for the document (for writer documents)
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | ||
| content | No | ||
| doc_type | No | writer |
Output Schema
| Name | Required | Description |
|---|---|---|
| path | Yes | Full path to the document |
| exists | Yes | Whether the file exists |
| format | Yes | Document format (odt, ods, odp, etc.) |
| filename | Yes | Document filename |
| size_bytes | Yes | File size in bytes |
| modified_time | Yes | Last modification time |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states this creates a document but doesn't mention whether this requires write permissions, what happens if a file already exists at the path, whether the operation is atomic, or what the output contains. The description provides basic functional information but lacks important behavioral context for a creation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear purpose statement followed by parameter explanations. Every sentence adds value: the first states what the tool does, and the subsequent lines explain each parameter's purpose. There's no wasted text or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a creation tool with no annotations but with an output schema (which handles return values), the description is moderately complete. It explains the parameters well but lacks behavioral context about permissions, file overwriting, or error conditions. The presence of an output schema means the description doesn't need to explain return values, but for a mutation tool, more behavioral guidance would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates well by explaining all three parameters: 'path' (full path where document should be created), 'doc_type' (type with specific options listed), and 'content' (initial content for writer documents). It adds meaningful context beyond the bare schema, though it could clarify that 'content' only applies to 'writer' type documents.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Create' and resource 'new LibreOffice document', making the purpose immediately understandable. It distinguishes from siblings like 'open_document_in_libreoffice' or 'read_document_text' by focusing on creation rather than opening or reading existing documents. However, it doesn't explicitly differentiate from 'create_live_editing_session' which also creates something.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. There's no mention of prerequisites, when not to use it, or comparison to sibling tools like 'create_live_editing_session' or 'open_document_in_libreoffice'. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
create_live_editing_sessionC
Create a live editing session with automatic refresh capabilities
Args:
path: Path to the document for live editing
auto_refresh: Whether to enable automatic refresh detection
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | ||
| auto_refresh | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
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 mentions 'automatic refresh capabilities' but doesn't explain what this entails, such as how often refreshes occur or what triggers them. Critical details like permissions required, whether the session is persistent, or potential side effects are missing, leaving significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured, with a clear purpose statement followed by a brief parameter list. Each sentence serves a purpose, and there's no unnecessary verbosity, making it easy to scan and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (creating a live editing session) and the presence of an output schema, the description is moderately complete. It covers the basic purpose and parameters but lacks details on behavioral aspects like session management or refresh behavior. The output schema likely handles return values, so the description doesn't need to explain those, but it should provide more context on usage and limitations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal semantics beyond the input schema, which has 0% coverage. It briefly explains 'path' as 'Path to the document for live editing' and 'auto_refresh' as 'Whether to enable automatic refresh detection', but this doesn't fully compensate for the lack of schema descriptions. For example, it doesn't specify the format of 'path' or what 'automatic refresh detection' means in practice, leaving parameters partially unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create a live editing session') and the resource ('document for live editing'), specifying the tool's purpose. However, it doesn't distinguish this tool from potential siblings like 'create_document' or 'watch_document_changes', which might involve similar document operations but with different functionalities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description lacks context about prerequisites, such as whether the document must exist or be accessible, and doesn't mention any sibling tools like 'create_document' or 'watch_document_changes' that might serve overlapping purposes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
_docx_has_ommlA
检测 docx 是否含 OMML 公式(word/document.xml 里查 <m:oMath)。
2026-10-24:LibreOffice 对 OMML 的 run 字号(m:r/w:rPr/w:sz)完全忽略,
公式全部按 Math 组件默认基准字号渲染(LO Bug 32419,多年未修)——
含公式的 docx 用 LO 转 PDF,公式字号/溢出判断全部失真。
含公式 → 路由 Word COM(真渲染);无公式 → LO 照旧(快)。
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does so well: it explains why the check exists (LO Bug 32419 ignores m:r/w:rPr/w:sz, so formula font size and overflow judgments are distorted), which tells the agent the practical consequence of a false negative. It omits error behavior for missing/non-docx paths and whether the check is cheap or does full XML parsing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Purpose is front-loaded in the opening line, followed by the rationale and the routing rule. The dated changelog framing ('2026-10-24') and bug number are slightly noisy, but each sentence supports the routing decision rather than padding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter boolean predicate with an output schema, the description supplies enough: what is checked, why it matters, and what to do with each outcome. Only edge-case behavior (invalid path, non-docx input, relative vs absolute paths) is left unspecified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter has 0% schema description coverage — the schema only supplies type string with format path. The description implies the path targets a docx but never states whether it must be an absolute local path, a workspace-relative path, or what happens for non-.docx files, so the gap is only partially compensated.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The first sentence states a specific verb and resource: detect whether a docx contains OMML formulas, and even names the exact XML location checked (word/document.xml, <m:oMath>). This is a narrow predicate tool, and its scope is unambiguous relative to conversion or text-reading siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit branching guidance: formulas present → route to Word COM for true rendering; absent → use LibreOffice as usual for speed. That is a clear use/no-use decision. It stops short of naming the sibling tools (batch_convert_documents, open_document_in_libreoffice) that the routing decision feeds into.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_document_infoC
Get detailed information about a LibreOffice document
Args:
path: Path to the document file
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| path | Yes | Full path to the document |
| exists | Yes | Whether the file exists |
| format | Yes | Document format (odt, ods, odp, etc.) |
| filename | Yes | Document filename |
| size_bytes | Yes | File size in bytes |
| modified_time | Yes | Last modification time |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool gets 'detailed information' but doesn't specify what that includes (e.g., metadata, structure, content), whether it's read-only, or any performance or permission considerations. This leaves significant gaps for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with two sentences: a purpose statement and a parameter explanation. It's front-loaded with the main function, though the 'Args' section could be integrated more smoothly. Overall, it avoids unnecessary verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which handles return values), no annotations, and a simple parameter structure, the description is minimally adequate. It covers the basic purpose and parameter, but lacks usage guidance and behavioral details, making it incomplete for optimal agent understanding in a context with many sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description includes an 'Args' section that documents the single parameter 'path', adding meaning beyond the input schema which has 0% description coverage. However, it only states 'Path to the document file' without clarifying format (e.g., absolute/relative, file extensions) or constraints, providing basic but incomplete compensation for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and resource 'detailed information about a LibreOffice document', making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_document_statistics' or 'read_document_text', which appear to serve similar informational purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. With siblings like 'get_document_statistics' and 'read_document_text' available, the description lacks any indication of what distinguishes this tool or when it should be preferred over others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_document_statisticsC
Get detailed statistics about a document
Args:
path: Path to the document file
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'Get[s] detailed statistics' but doesn't specify what types of statistics (e.g., word count, page count, file size), whether it's read-only or has side effects, or any performance or permission considerations. This leaves significant gaps for a tool that likely interacts with documents.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the core purpose stated first in a clear sentence. The additional 'Args' section is concise and relevant, though it could be integrated more smoothly. There's no wasted text, making it efficient for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (single parameter, no annotations, but with an output schema), the description is minimally adequate. The output schema likely covers return values, reducing the need for detailed output explanations. However, it lacks context on statistics types, usage distinctions from siblings, and behavioral traits, leaving room for improvement in guiding the agent effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal semantics beyond the input schema, which has 0% description coverage. It mentions 'path: Path to the document file', clarifying the parameter's purpose, but doesn't provide format details (e.g., absolute vs. relative paths, supported file types) or examples. With one parameter and low schema coverage, this offers some compensation but remains basic.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get') and resource ('detailed statistics about a document'), making it immediately understandable. However, it doesn't explicitly distinguish this tool from sibling tools like 'get_document_info' or 'read_document_text', which might provide overlapping or related functionality, preventing a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. With siblings like 'get_document_info' and 'read_document_text' available, there's no indication of what makes 'get_document_statistics' unique or appropriate for specific scenarios, leaving the agent to guess based on tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
insert_text_at_positionB
Insert text into a LibreOffice Writer document
Args:
path: Path to the document file
text: Text to insert
position: Where to insert the text ("start", "end", or "replace")
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | ||
| text | Yes | ||
| position | No | end |
Output Schema
| Name | Required | Description |
|---|---|---|
| path | Yes | Full path to the document |
| exists | Yes | Whether the file exists |
| format | Yes | Document format (odt, ods, odp, etc.) |
| filename | Yes | Document filename |
| size_bytes | Yes | File size in bytes |
| modified_time | Yes | Last modification time |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only minimally addresses behavior. It mentions 'insert' implies mutation but doesn't disclose critical traits like whether changes are saved automatically, permission requirements, error handling, or side effects on document formatting. This leaves significant gaps for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear purpose statement followed by a bullet-point list of parameters. Every sentence earns its place without redundancy, making it easy to scan and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a mutation tool with no annotations, 3 parameters, and an output schema (which reduces need to describe returns), the description is minimally adequate. It covers the basics but lacks depth on behavioral context, error conditions, and integration with sibling tools, leaving room for improvement.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 lists all three parameters with brief explanations, adding value beyond the bare schema. However, it doesn't elaborate on format details (e.g., path syntax, text encoding, position enum meanings beyond listing them), keeping it at a baseline level.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Insert text') and resource ('into a LibreOffice Writer document'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'merge_text_documents' or 'create_document', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 like 'create_document' or 'merge_text_documents'. It lacks context about prerequisites (e.g., document must exist) or exclusions, offering only basic parameter explanations without usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
merge_text_documentsA
Merge multiple text documents into a single document
Args:
document_paths: List of paths to documents to merge
output_path: Path where merged document should be saved
separator: Text to insert between merged documents
| Name | Required | Description | Default |
|---|---|---|---|
| separator | No | --- | |
| output_path | Yes | ||
| document_paths | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| path | Yes | Full path to the document |
| exists | Yes | Whether the file exists |
| format | Yes | Document format (odt, ods, odp, etc.) |
| filename | Yes | Document filename |
| size_bytes | Yes | File size in bytes |
| modified_time | Yes | Last modification time |
TDQS
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 mentions that documents are merged and saved, implying a write operation, but lacks details on permissions, error handling, file format support, or what happens if output_path exists. This is insufficient for a mutation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose in the first sentence, followed by a structured Args section that efficiently documents parameters without redundancy. Every sentence serves a clear purpose, making it appropriately sized and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 parameters, mutation operation) and the presence of an output schema (which handles return values), the description covers the basic operation and parameters. However, it lacks behavioral context like file handling or error scenarios, making it adequate but incomplete for safe usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 lists all three parameters (document_paths, output_path, separator) with brief explanations, adding meaning beyond the schema's titles. However, it doesn't specify path formats or separator usage details, leaving some gaps in semantic clarity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Merge multiple text documents') and the resource ('into a single document'), distinguishing it from siblings like 'batch_convert_documents' or 'create_document' which involve different operations. It directly answers what the tool does without being vague or tautological.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 like 'create_document' or 'insert_text_at_position', nor does it mention prerequisites or exclusions. It states what the tool does but offers no context for selection among the available document manipulation tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
open_document_in_libreofficeA
Open a document in LibreOffice GUI for live viewing
Args:
path: Path to the document to open
readonly: Whether to open in read-only mode (default: False)
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | ||
| readonly | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the tool opens a document in LibreOffice GUI for live viewing, which implies a user interface interaction and potential resource usage. However, it doesn't mention behavioral traits like whether it launches a new instance, handles errors for invalid paths, or requires LibreOffice installation, leaving gaps in understanding the tool's operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose in the first sentence, followed by a structured 'Args:' section that efficiently documents parameters. Every sentence adds value without redundancy, making it appropriately sized and easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 parameters, no annotations, but has an output schema), the description is mostly complete. It covers the purpose and parameters adequately, but since an output schema exists, it doesn't need to explain return values. However, it could benefit from more behavioral context, such as error handling or prerequisites, to be fully comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 adds meaning by explaining 'path' as 'Path to the document to open' and 'readonly' as 'Whether to open in read-only mode (default: False)', which clarifies the purpose and default behavior beyond the bare schema. However, it doesn't detail path format constraints or read-only implications, keeping it from a perfect score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Open a document in LibreOffice GUI for live viewing'), identifies the resource ('document'), and distinguishes it from siblings like 'create_document' or 'read_document_text' by emphasizing GUI interaction and live viewing. It provides a verb+resource combination that is precise and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for opening documents in LibreOffice GUI, which suggests it's for interactive viewing rather than batch processing or conversion (contrasted with siblings like 'batch_convert_documents' or 'convert_document'). However, it lacks explicit guidance on when not to use it or direct alternatives, such as 'refresh_document_in_libreoffice' for already open documents.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
read_document_textC
Extract text content from a LibreOffice document
Args:
path: Path to the document file
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| content | Yes | The extracted text content |
| char_count | Yes | Number of characters in the content |
| page_count | Yes | Number of pages (if available) |
| word_count | Yes | Number of words in the content |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states the basic action. It doesn't disclose behavioral traits like error handling (e.g., for invalid paths or unsupported formats), performance aspects (e.g., large file handling), or output specifics (though an output schema exists). This leaves gaps in understanding the tool's operation beyond its core function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with two sentences: one stating the purpose and another listing the parameter. It's front-loaded with the main action, though the parameter section is brief. There's no wasted text, making it efficient for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one parameter) and the presence of an output schema, the description is minimally complete. However, it lacks details on error cases, file format support, or integration with sibling tools, which could aid an agent in correct invocation. It meets basic needs but leaves room for improvement in contextual guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal semantics beyond the input schema, which has 0% coverage. It only repeats the parameter name 'path' without explaining format (e.g., absolute vs. relative), constraints, or examples. With one parameter and low schema coverage, the description provides basic context but doesn't fully compensate for the lack of detailed documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'extract' and resource 'text content from a LibreOffice document', making the purpose specific and understandable. It distinguishes from siblings like 'read_spreadsheet_data' by specifying document text extraction, though it doesn't explicitly differentiate from 'get_document_info' or 'get_document_statistics'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 like 'get_document_info' (which might include metadata) or 'read_spreadsheet_data' (for spreadsheet content). It lacks context about prerequisites, such as file accessibility or format support, offering only basic usage without exclusions or comparisons.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
read_impress_layoutA
精确读取 PPT(.pptx)每页每个元素的几何布局:坐标/宽高(厘米)、旋转、占位符角色、z 序、组内子元素、文本摘要。
三层 z 序:masters(最底层装饰) < layouts(版式装饰) < 页面 shapes(最顶层)。
重叠/遮挡判断必须三层合并——"标题压住橙色块"这类问题,装饰块在版式/母版上,只看页面形状查不出来。
页面元素几何为 None 表示未显式设置(继承版式占位符位置)。
用于回答"这个元素在页面哪里/多大面积/有没有重叠出界/层级谁压谁"——read_document_text 只给文字流,
位置信息在文本转换时全部丢失。仅支持 .pptx;.ppt/.odp 先用 convert_document 转 pptx 再读。
Args:
path: PPT 文件路径(.pptx)
slides: 可选,页码过滤,如 "1" 或 "1,3-5";缺省读全部页
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | ||
| slides | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| path | Yes | |
| slides | Yes | |
| layouts | No | 版式装饰清单(z 序介于母版与页面形状之间) |
| masters | No | 母版装饰清单(z 序最底层) |
| slides_total | Yes | |
| slide_width_cm | Yes | 页面宽(厘米) |
| slide_height_cm | Yes | 页面高(厘米) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and does well: it discloses the non-obvious three-layer z-order model (masters < layouts < slide shapes), warns that overlap judgments must merge all three layers because decorative blocks live on layouts/masters, and explains that geometry of None means the value is not explicitly set and is inherited from a layout placeholder. It does not cover performance on large decks or how images/charts are represented, which is why it falls short of 5.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core capability before the z-order nuance and the sibling comparison, and every claim carries practical weight. The z-order section is slightly verbose, but it encodes information an agent could not infer otherwise, so it largely earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Return format does not need explaining because an output schema exists. Combined with explicit format restrictions, the usage scenario, the inheritance caveat, and the routing to convert_document, an agent has everything it needs in order to call this tool correctly and to know when not to.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate, and it does: path is identified as the .pptx path, and slides is documented as an optional page filter with concrete syntax examples ("1", "1,3-5") and a stated default of reading all pages. Minor gap: path is not described in terms of relative vs absolute paths or error behavior for a missing or non-.pptx file.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description gives a specific verb (精确读取) and a precisely scoped resource: the per-element geometry for each slide of a .pptx file, enumerated as coordinates, size in cm, rotation, placeholder role, z-order, group children, and text summary. It then explicitly sets itself apart from read_document_text by saying that one only returns a text stream and loses all position data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It states the exact questions this tool answers (where an element sits, how large it is, whether it overlaps or exceeds bounds, and which element covers which), names the competing sibling read_document_text and why that sibling is insufficient, and gives an explicit fallback path: convert .ppt/.odp to pptx with convert_document first. The exclusions are unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
read_spreadsheet_dataA
Read data from a LibreOffice Calc spreadsheet
Args:
path: Path to the spreadsheet file (.ods, .xlsx, etc.)
sheet_name: Name of the specific sheet to read (if None, reads first sheet)
max_rows: Maximum number of rows to read (default 100)
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | ||
| max_rows | No | ||
| sheet_name | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| data | Yes | 2D array of cell values |
| col_count | Yes | Number of columns |
| row_count | Yes | Number of rows |
| sheet_name | Yes | Name of the sheet |
TDQS
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 describes a read operation with parameters but lacks details on permissions, file access requirements, error handling, or output format. While it implies a non-destructive read, it does not explicitly state safety aspects like whether it modifies the file or has rate limits, leaving significant gaps for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose, followed by a structured list of parameters with clear explanations. Every sentence adds value without redundancy, and the format is efficient for quick comprehension, making it appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema, the description does not need to explain return values. However, with no annotations and 0% schema description coverage, it partially compensates with parameter semantics but lacks behavioral context like error cases or performance limits. It is adequate for a read operation but has clear gaps in safety and usage guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, so the description must compensate. It adds meaningful semantics for all three parameters: path specifies file types (.ods, .xlsx), sheet_name clarifies behavior when None (reads first sheet), and max_rows defines a default (100). This goes beyond the bare schema, though it could provide more context on path validation or max_rows constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Read data from') and resource ('LibreOffice Calc spreadsheet'), distinguishing it from sibling tools like read_document_text or get_document_info that handle different document types or operations. It precisely defines what the tool does without being vague or tautological.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 like read_document_text (for text documents) or get_document_info (for metadata). It mentions default behavior for sheet_name and max_rows but does not specify use cases, prerequisites, or exclusions, leaving the agent to infer usage from context alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
refresh_document_in_libreofficeB
Send a refresh signal to LibreOffice to reload a document
Args:
path: Path to the document that should be refreshed
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'refresh signal' and 'reload a document', implying a read-only or update operation, but fails to detail critical aspects like whether this requires LibreOffice to be running, if it affects unsaved changes, error handling, or response behavior. This leaves significant gaps for a tool interacting with external software.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded with the main purpose in the first sentence, followed by parameter details. It avoids unnecessary words, though the structure could be slightly improved by integrating the parameter explanation more seamlessly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (interacting with LibreOffice), lack of annotations, and presence of an output schema (which reduces need to explain returns), the description is minimally adequate. It covers the basic action and parameter but misses important contextual details like dependencies on LibreOffice state or error scenarios, making it incomplete for safe use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful context for the single parameter 'path' by specifying it as 'Path to the document that should be refreshed', which clarifies its role beyond the schema's basic type. With 0% schema description coverage and only one parameter, this compensates adequately, though it could include format examples (e.g., file paths).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Send a refresh signal') and the resource ('to LibreOffice to reload a document'), making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'open_document_in_libreoffice' or 'watch_document_changes', which might involve similar document-handling operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 lacks context such as prerequisites (e.g., document must be open in LibreOffice), exclusions, or comparisons to siblings like 'open_document_in_libreoffice' for initial loading or 'watch_document_changes' for monitoring updates.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_documentsC
Search for documents containing specific text
Args:
query: Text to search for
search_path: Directory to search in (default: common document locations)
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | ||
| search_path | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
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 mentions the search functionality but doesn't describe what 'search' entails—whether it's case-sensitive, supports regex, returns partial matches, or includes metadata in results. It also omits performance characteristics like speed, rate limits, or error conditions, which are critical for a search operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the core purpose in the first sentence and parameter details following. There's no wasted text, but the structure could be slightly improved by integrating parameter explanations more seamlessly rather than a separate 'Args:' section, though this is minor.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 parameters, no annotations, but with an output schema), the description is minimally adequate. The output schema likely covers return values, reducing the need for result explanation. However, for a search tool, it should better address behavioral aspects like search scope and limitations, which are missing, making it incomplete for optimal agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 adds basic semantics for both parameters: 'query' as 'Text to search for' and 'search_path' with a default and scope hint ('common document locations'). This clarifies intent beyond the bare schema, but lacks details like format examples, path validation rules, or query syntax, leaving gaps in practical usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Search') and resource ('documents'), and specifies the search criteria ('containing specific text'). It distinguishes itself from siblings like 'read_document_text' or 'get_document_info' by focusing on text-based search rather than direct reading or metadata retrieval. However, it doesn't explicitly differentiate from potential overlapping tools like 'watch_document_changes' in terms of search scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 doesn't mention when to prefer this over 'read_document_text' for content extraction or 'get_document_info' for metadata-based filtering. There's no context about prerequisites, limitations, or typical use cases, leaving the agent to infer usage from the purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
watch_document_changesB
Watch a document for changes and provide live updates
Args:
path: Path to the document to watch
duration_seconds: How long to watch for changes (default: 30 seconds)
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | ||
| duration_seconds | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
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 mentions 'live updates' and a duration, but lacks details on how updates are delivered (e.g., streaming, polling), what constitutes a 'change', permissions required, rate limits, or whether it's a blocking call. This is inadequate for a tool that likely involves real-time monitoring.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the core purpose stated first. The parameter explanations are brief and directly relevant. However, the 'Args:' section could be integrated more seamlessly, and some sentences might benefit from additional context to enhance clarity without adding bulk.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (real-time monitoring) and lack of annotations, the description is minimally adequate. It covers the basic action and parameters but misses behavioral details like update mechanisms or error handling. The presence of an output schema helps, but the description doesn't reference it, leaving gaps in understanding the full tool behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 adds meaningful context for both parameters: 'path' is explained as 'Path to the document to watch', and 'duration_seconds' as 'How long to watch for changes (default: 30 seconds)'. This clarifies their roles beyond the bare schema, though it doesn't detail path formats or duration constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Watch a document for changes and provide live updates.' It specifies the verb ('watch'), resource ('document'), and outcome ('live updates'), making it easy to understand. However, it doesn't explicitly differentiate from siblings like 'get_document_info' or 'refresh_document_in_libreoffice', which might also involve document monitoring or updates.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 the action but doesn't specify scenarios (e.g., for real-time collaboration vs. static analysis) or compare it to siblings like 'create_live_editing_session' or 'refresh_document_in_libreoffice', leaving the agent to infer usage from context alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
15 tool updates
v0.1.0- First observed
_docx_has_omml - First observed
batch_convert_documents - First observed
create_document - First observed
create_live_editing_session - First observed
get_document_info - First observed
get_document_statistics - First observed
insert_text_at_position - First observed
merge_text_documents - First observed
open_document_in_libreoffice - First observed
read_document_text - First observed
read_impress_layout - First observed
read_spreadsheet_data - First observed
refresh_document_in_libreoffice - First observed
search_documents - First observed
watch_document_changes
TDQS
Scored across 15 tools
Most tools target distinct document operations and file types, so selection is generally clear. However, get_document_info overlaps with get_document_statistics, the live-editing cluster (open/refresh/watch/create_live_editing_session) has some boundary ambiguity, and _docx_has_omml looks like an internal helper exposed as a tool.
Nearly all tools use snake_case with predictable verb_noun phrasing, such as create_document, read_document_text, and merge_text_documents. The main deviations are the internal-looking _docx_has_omml name and the adjective-prefixed batch_convert_documents, but the set remains mostly consistent.
Fifteen tools is within the expected well-scoped range and covers reading, writing, conversion, search, and live-viewing workflows. The count is not excessive, though one exposed internal helper slightly dilutes the set.
The surface covers document creation, reading, search, batch conversion, and Writer text insertion, but editing support is thin for Calc and Impress. There are no clear tools for updating spreadsheet cells, modifying slides, deleting documents, or general single-document export/save workflows.
Maintenance
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Convert, create and edit Word, PowerPoint, Excel and PDF documents from any AI agent.
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Document conversion MCP server: PDF to Markdown, image OCR, spreadsheet parsing.
Document processing over MCP: merge, split and compress PDFs, run OCR, extract document text.
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