Word Counter — Count words, characters, sentences, paragraphs, and reading time in a text or uploaded document (.txt/.pdf/.docx). [category: analyze]
| Name | Required | Description | Default |
|---|---|---|---|
| file | No | Alternative: upload a .txt, .pdf, or .docx document (max 25MB). | |
| text | Yes | Text to analyse. Required unless 'file' is provided. |
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 declare readOnlyHint=true, so the read-only nature is established. The description adds that the tool handles text or .txt/.pdf/.docx uploads and computes several count-based metrics, which clarifies scope but adds little about side effects, processing limits, or return behavior beyond what annotations and schema already imply.
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 efficient sentence with a clear em-dash lead-in, front-loading the core action and metrics. It is slightly redundant with the title and includes a category tag, but overall there is minimal waste.
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 low-complexity, read-only analysis tool, the description covers the resource type, supported formats, and what it counts. Since there is no output schema, it would help to explicitly state the return shape, but the metric enumeration makes the expected result reasonably inferable.
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 schema fully documents the 'text' and 'file' parameters. The description adds the list of computed metrics and the supported document formats, but these are mostly redundant with the schema and title; it does not deepen parameter understanding.
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 states a specific action ('Count') and resource (text or uploaded document), and enumerates the counted metrics. It distinguishes itself from siblings like analyze_word_frequency and analyze_readability by listing characters, sentences, paragraphs, and reading time, though it does not explicitly name an alternative tool.
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 about when to use this tool versus alternatives such as analyze_word_frequency or analyze_grammar_check. The usage context is only implied by the tool name and metric list; there are no exclusions, prerequisites, or explicit routing instructions.
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.
