Barcode Generator — Generate a barcode (Code128, EAN-13, DataMatrix, PDF417, etc.) as a PNG image. [category: generate]
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | Symbology. Unknown types fall back to code128. | code128 |
| height | No | Output height in px. Width is derived automatically (height×3; square for qr/datamatrix) — there is no 'width' parameter. | |
| content | Yes | The data to encode |
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 already mark the tool as generative and non-destructive, and the description adds the key output trait: the result is a PNG image. For a low-risk generation tool this covers the main behavioral contract, though it does not explain how the image is returned.
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 key action and output format are front-loaded in a short, readable sentence, with schema details left to the structured fields. The opening 'Barcode Generator' duplicates the title and the [category: generate] tag is marginal, so it is not a perfect 5.
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?
With all parameters described in the schema and the description naming the PNG output, an agent has enough information to invoke this tool correctly for a simple generation task. The main missing piece is guidance for QR-only requests, which could otherwise be routed to generate_qr_code.
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 input schema documents all three parameters, including defaults, bounds, and the type enum, so the baseline applies. The description adds only a few human-readable symbology examples without contributing new constraints beyond the schema.
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 (generate a barcode), the resource, and the output format (PNG), and gives example symbologies that signal scope. It does not explicitly distinguish itself from the closely related sibling generate_qr_code, so it stops short of 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 about when to use this tool instead of alternatives such as generate_qr_code, nor does it mention that the schema supports QR. The only usage hint is the generic [category: generate] tag, which is not sufficient for an agent to route between related generators.
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.
