Describe Image — Look at an image with a vision model and answer a question about it — what it shows, whether it's blurry or usable, visible text, etc. Business plan only. [category: content] [requires the business plan]
| Name | Required | Description | Default |
|---|---|---|---|
| file | Yes | The image to look at | |
| question | No | What to answer about the image (optional — defaults to a concise description) |
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?
The description supplements the readOnlyHint annotation by explaining the underlying mechanism (vision model) and gives concrete behavioral examples such as detecting blurriness or visible text. It also discloses the business plan access requirement. No contradiction with annotations.
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 short, front-loaded, and easy to parse. The only minor redundancy is that the business plan requirement appears both in prose and as bracketed metadata, which slightly weakens editorial precision.
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 read-only image description tool, the description covers the tool's purpose, mechanism, access restriction, and typical use cases. It does not specify the exact output format, but 'answer a question' adequately implies a text response.
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 already fully documents both parameters, including that question is optional and defaults to a concise description. The description adds illustrative examples of what the question can cover, but those are helpful examples rather than essential semantic details.
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: look at an image with a vision model and answer a question about it. It gives concrete examples of what the tool can report (contents, blurriness, usability, visible text). However, it does not explicitly distinguish itself from overlapping siblings like analyze_image_quality or photo_to_text.
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 use case is implied: use when you need a natural-language answer or description of an image's contents. There is no explicit when-to-use versus alternatives guidance, and the only explicit constraint is the business plan requirement.
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.
