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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
extract_text_from_fileC

从文档文件中提取文字内容,支持 PDF、Word、TXT、MD 等格式

generate_wordcloudC

根据文字内容生成词云图

create_wordcloud_from_fileC

从文档文件直接生成词云图(提取文字 + 生成词云图的组合操作)

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

B3/5.0

Scored across 3 tools

Disambiguation2/5

The tools have significant overlap and unclear boundaries. 'create_wordcloud_from_file' combines extraction and generation, while 'extract_text_from_file' and 'generate_wordcloud' are its components, making them redundant and confusing for an agent to choose between. This overlap creates ambiguity about when to use the combined tool versus the separate ones.

Naming Consistency5/5

All tool names follow a consistent snake_case pattern with clear verb_noun structure (e.g., create_wordcloud_from_file, extract_text_from_file, generate_wordcloud). The naming is predictable and readable across the set, with no deviations in style or convention.

Tool Count3/5

With 3 tools, the count is borderline thin for a word cloud domain, as it might lack advanced features like customization or analysis. However, it covers basic operations, so it's not severely mismatched but feels minimal and could benefit from additional tools for a more complete workflow.

Completeness3/5

The tools cover core word cloud creation from files and text, but there are notable gaps. Missing operations include customizing word cloud parameters (e.g., colors, shapes), saving/output options, or analyzing word frequencies. The surface allows basic generation but lacks flexibility for more complex agent tasks.

Maintenance

ActivityInactive
ResponsivenessNo issues