Lorem Ipsum Generator — Generate lorem ipsum placeholder text by word count or paragraph count. [category: generate]
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | Unit to generate. Field names are 'type' + 'count' — 'paragraphs'/'words_per_paragraph' do not exist. | paragraphs |
| count | No | How many words/sentences/paragraphs to generate. | |
| startLorem | No | Start with the classic 'Lorem ipsum dolor sit amet' opening. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide little safety context (readOnlyHint: false, destructiveHint: false), so the description carries the burden. It adds that generation is driven by word or paragraph count, but it does not disclose whether the output is plain text, whether it is returned directly to the caller, or whether any file is created. For a simple generator this is a modest but acceptable transparency level.
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 a single front-loaded clause followed by a category tag, with no filler or redundant explanation. It is appropriately sized for a simple tool, even though it omits one supported mode, which is an accuracy issue rather than a conciseness issue.
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 simple generator with fully documented parameters and no output schema, the description covers the core purpose and main modes. Missing details such as exact return format or whether output is a file are not clearly stated, but 'placeholder text' strongly implies the result is returned text, making the definition mostly complete.
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 100%, so the baseline is 3. The description adds little beyond the schema; it reinforces the concept of count-based generation but does not explain parameter interplay or the startLorem option, which the schema already documents adequately.
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 identifies the tool as generating lorem ipsum placeholder text and mentions word/paragraph count modes, so the resource and action are specific. However, it does not explicitly differentiate from sibling generators such as generate_placeholder_image, and it omits the 'sentences' mode that the schema supports, making it slightly incomplete.
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 no guidance on when to use this tool versus related alternatives like generate_placeholder_image or other text-generating tools. There are no when/when-not conditions or explicit exclusions; the intended usage must be inferred from the resource name and context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Multiple tool pairs are near-identical: octopus_mkdir/octopus_make_folder and octopus_move/octopus_move_file are literal duplicates, analyze_hash/generate_hash both compute hashes, convert_word_to_pdf overlaps convert_document, and photo_compress/photo_compress_to_size plus pdf_thumbnails/pdf_to_images have fuzzy boundaries. The descriptions are detailed and cross-reference each other helpfully, but at 144 tools an agent will regularly misselect.
The dominant {category}_{verb}_{object} snake_case pattern (pdf_*, photo_*, convert_*, analyze_*, media_*) is largely consistent and predictable. However, outliers like chatwithyourpdf and describe_image break the category-prefix convention, and the octopus namespace mixes bare verbs (read, write, mkdir) with verb_noun forms (make_folder, move_file, search_meta) inconsistently.
144 tools is an extreme count for any MCP server. The broad scope (PDF, photo, video, audio, conversion, analysis, generation, file storage, web, e-sign) justifies some volume, but the count is inflated by batch and inspect variants (pdf_to_excel + batch + inspect), duplicate tools, and overlapping converters. An agent faces an overwhelming selection surface.
Per-domain coverage is remarkably deep: PDF spans merge/split/compress/protect/unlock/metadata/OCR/watermark and bidirectional conversion; photo covers editing, format conversion, face handling, OCR, and collage; file storage has full CRUD plus search. Minor gaps exist (no audio transcription, no video metadata editing, no deletion of PDF pages is actually covered via pdf_delete_pages) but the surface has no dead ends for its declared domains.
