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analyze_duplicate_detector

Read-only

Duplicate Detector — Identify duplicate or near-duplicate files in a batch upload using perceptual hashing. [category: analyze]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filesYes2-20 files to compare (any type). Files beyond the first 20 are silently ignored.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds value by disclosing the perceptual-hashing mechanism, which implies approximate matching rather than byte-level comparison. It does not disclose result format, similarity threshold, or behavior on mixed file types, but the schema's note about silently ignoring files beyond 20 covers the main edge case.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single tight sentence that front-loads the purpose before the method. The 'Duplicate Detector —' prefix slightly redundantly repeats the tool name, but there is no other wasted content, and the key discriminator (perceptual hashing) is included.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter, read-only analyze tool with a fully documented schema, the definition covers the essential context: what it does, how it does it, and the input constraints. The main gaps — return value shape and near-duplicate threshold — are minor for an analyze-category tool with no output schema and would likely be observable at runtime.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%: the 'files' parameter already documents the 2-20 range, accepted types, and silent-ignore behavior. The description's 'batch upload' phrasing adds minor framing but no new semantic detail beyond the schema, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Identify'), a specific resource ('duplicate or near-duplicate files in a batch upload'), and the method ('perceptual hashing'). This distinguishes it from siblings like analyze_hash (plain hashing) and analyze_image_similarity (image-specific similarity) — an agent can tell what this tool does without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'in a batch upload' implies the intended scenario (comparing a set of files at once), and the schema's 2-20 file range reinforces this. However, the description gives no explicit when-to-use vs. when-not-to-use guidance and names no alternatives, leaving the agent to infer the boundary against near-siblings like analyze_image_similarity and analyze_hash.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.2/5.0
Disambiguation2/5

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.

Naming Consistency3/5

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.

Tool Count2/5

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.

Completeness4/5

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.

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