John's Essentials

generate_invoice

Invoice Generator — Generate a professional PDF invoice from line items, client details, and company info. Takes a JSON body (camelCase fields), not form fields. [category: generate]

Input Schema

TableJSON Schema

Name	Required	Description	Default
`items`	Yes	Line items. Keys MUST be description/quantity/unitPrice — other keys are silently ignored and amounts render as 0.
`notes`	No	Wrapped text under a 'Notes / Terms' heading at the bottom; empty hides the section.
`dueDate`	No	Free text printed as 'Due: <value>' — never parsed or validated; empty hides the line.
`currency`	No	Sets the printed symbol ONLY — no conversion. Unknown codes print '$'; INR prints 'Rs'.	USD
`clientName`	Yes	Client name (REQUIRED). Field name is 'clientName' — not 'client_name'.
`taxPercent`	No	Percent of subtotal added on top. Unvalidated; the tax row appears only when greater than 0.
`clientEmail`	No	Printed in BILL TO under the client name; empty = line omitted. Never validated.
`companyName`	Yes	Issuing company name (REQUIRED).
`invoiceDate`	No	Free text printed as 'Date: <value>' — never parsed; empty hides the line.
`companyEmail`	No	Printed in the issuer header block; empty = line omitted. Never validated.
`companyPhone`	No	Printed in the issuer header block; empty = line omitted.
`clientAddress`	No	One printed line under BILL TO — no wrapping, so keep it short; empty = line omitted.
`invoiceNumber`	No	Auto-generated 'INV-<8hex>' when omitted.
`companyAddress`	No	One printed line in the issuer header — no wrapping; empty = line omitted.
`discountPercent`	No	Percent of subtotal subtracted. Unvalidated — over 100 yields a negative total. Row hidden when 0.

Schema Changelog

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

First observedSep 5, 2026

TDQS

A4.1/5.0

Behavior3/5

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

Annotations already signal readOnlyHint=false and destructiveHint=false; the description adds that the tool produces a PDF and expects JSON input. It doesn't disclose return/delivery behavior, auth requirements, or side effects, but the core output type is stated and no contradiction with annotations exists.

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?

The description is short and front-loads the main action, with no filler beyond the useful '[category: generate]' tag. It loses one point because 'Invoice Generator —' mostly duplicates the annotation title, creating slight redundancy before the actual verb.

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?

This is a 15-parameter tool with no output schema, but the schema descriptions cover required fields, defaults, formatting quirks, and conditional rendering, making the input side very complete. The description supplies the key JSON/camelCase framing and output type; only the exact return/delivery mechanism is left underspecified.

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

Parameters4/5

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

Schema coverage is 100% and the individual parameter descriptions are unusually rich, so the baseline is 3. The description adds meaningful invocation-level semantics—JSON body, camelCase fields, not form fields—and groups the inputs into line items, client details, and company info, which goes beyond what the schema alone provides.

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 opens with a specific verb and resource: 'Generate a professional PDF invoice' from line items, client details, and company info. This makes the tool immediately distinguishable from sibling generate_* tools such as generate_certificate or generate_barcode without requiring schema inspection.

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?

It clearly sets the invocation context by stating the tool takes a JSON body with camelCase fields, not form fields, which is a critical calling-convention detail. It doesn't explicitly name alternatives or when-not-to-use, but among the sibling list it is the only invoice generator, so the intended usage context is clear.

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.

Resources

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