John's Essentials

pdf_to_excel_inspect

Read-only

PDF to Excel Inspector — Non-destructive scan of a PDF's tables before converting: per-table row/column counts, confidence flags, warnings. [category: pdf]

Input Schema

TableJSON Schema

Name	Required	Description	Default
`file`	Yes	The PDF to scan (multipart field 'file', 25MB cap). Runs real extraction but returns JSON metadata only — nothing is converted.
`pages`	No	Optional page range
`engine`	No	Table detection engine; invalid values fall back to auto.	auto
`ocrLang`	No	OCR language (Tesseract code).	eng
`ocrFirst`	No	Run OCR before table extraction (scanned PDFs).
`tableIndexes`	No	Comma-separated 0-based table indexes to keep. Empty = all tables.

Schema Changelog

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

First observedSep 5, 2026

TDQS

A4.4/5.0

Behavior5/5

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

The description and file param explicitly disclose that the tool runs real extraction but returns only JSON metadata and converts nothing, adding behavioral nuance beyond the readOnlyHint annotation. It also communicates output characteristics (confidence flags, warnings) without contradicting annotations.

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

Conciseness5/5

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

A single sentence front-loads the non-destructive nature and ends with a precise list of outputs. No fluff; every clause contributes.

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 read-only inspection tool with a fully documented 6-parameter schema, the description covers the output essence (counts, confidence, warnings, JSON only) and the file constraints. Without an output schema, a bit more detail on the exact response shape could help, but it's sufficient for selection and invocation.

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%, so the baseline applies; the description doesn't add much per-parameter meaning beyond the schema. The file parameter's note about multipart field and 25MB cap is a small addition, but overall the schema carries the semantics.

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 specifies a clear verb ('scan'), a specific resource (tables in a PDF), and a distinct scope ('before converting'), while listing concrete outputs (row/column counts, confidence flags, warnings). This differentiates it from conversion siblings like pdf_to_excel and pdf_to_excel_batch, and from generic pdf_file_info.

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

Usage Guidelines4/5

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

The phrase 'before converting' and 'Non-destructive scan' signal the intended use case as a pre-conversion inspection step. It does not explicitly name alternatives or exclusion conditions, but the context is clear enough for an agent to choose it over actual conversion tools.

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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