invoiceoracle
Server Details
InvoiceOracle - 10 e-invoicing tools: XRechnung, ZUGFeRD, Peppol, validation, archive.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- ToolOracle/invoiceoracle
- GitHub Stars
- 0
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Tool Definition Quality
Average 3.6/5 across 10 of 10 tools scored. Lowest: 3/5.
Tools have distinct purposes, but invoice_extract, invoice_summary, and invoice_validate overlap in extracted fields and validation. Descriptions clarify differences, but agents may still confuse extract vs summary.
All tools start with 'invoice_', but verb patterns are inconsistent: some are verbs (extract, validate), some nouns (health_check, tables), and some phrases (from_url, batch_urls). No uniform verb_noun pattern.
10 tools cover the full invoice processing pipeline—health check, extraction, OCR, tables, validation, ZUGFeRD—without unnecessary duplication. Well-scoped for the domain.
Covers core German invoice needs: field extraction, line items, validation, ZUGFeRD, OCR. Minor gaps like handling of foreign invoices or more granular search/filtering are missing but not critical for the stated purpose.
Available Tools
10 toolshealth_checkAInspect
InvoiceOracle server status and available library versions.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description implies read-only behavior, but lacks detail on safety, auth, or side effects. Adequate for simple health check.
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?
Single sentence, no filler, directly conveys purpose.
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?
Covers essential info for a health check, but could specify response format.
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?
No parameters, so description adds no param info. Baseline 4 applies.
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?
Description clearly states it checks server status and library versions. Distinct from sibling invoice tools.
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?
Usage is self-evident as a health check, but no explicit when-to-use or alternatives mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
invoice_batch_urlsAInspect
Process multiple invoice PDFs from URLs in one call. Returns analysis for each.
| Name | Required | Description | Default |
|---|---|---|---|
| urls | No | Comma-separated PDF URLs (max 10) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states the basic function; missing details on side effects, rate limits, error handling, or partial failure behavior.
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?
Two short, front-loaded sentences with no filler; each sentence adds value.
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?
Given no output schema, missing details about analysis content; behavioral aspects like concurrency or error handling not covered.
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 already describes the 'urls' parameter fully (comma-separated, max 10), so the description adds no additional semantic value beyond what the schema provides.
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 it processes multiple invoice PDFs from URLs in one call and returns analysis, distinguishing it from single-URL sibling tools like invoice_from_url.
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?
Implicitly suggests use for batch processing multiple invoices, but lacks explicit 'when to use' vs alternatives or 'when not to use' guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
invoice_extractBInspect
Smart field extraction from invoice: Rechnungsnummer, Datum, Fälligkeit, Gesamtbetrag, Netto, MwSt, IBAN, USt-IdNr., Steuernummer.
| Name | Required | Description | Default |
|---|---|---|---|
| pdf_path | No | Server-side file path to PDF (alternative to base64) | |
| pdf_base64 | No | Base64-encoded PDF content |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description lacks behavioral details such as whether the tool is read-only, requires authentication, or has rate limits. The term 'Smart field extraction' is vague and does not disclose processing behavior or error states.
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 sentence that efficiently lists the extracted fields. While it could be more structured (e.g., bullet points), it wastes no words and is front-loaded with the tool's purpose.
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?
The tool has no output schema, so the description should clarify the return format (e.g., JSON with field-value pairs). It only lists fields without stating how they are returned, leaving a significant gap for agent understanding.
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 describes both parameters (pdf_path and pdf_base64) with full coverage. The tool description adds no extra meaning beyond the schema, so a baseline of 3 is appropriate.
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 tool extracts specific invoice fields (e.g., Rechnungsnummer, Datum, Gesamtbetrag) from an invoice PDF. This verb-resource combination distinguishes it from sibling tools like invoice_ocr (pure OCR) or invoice_parse_text (text parsing).
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 description does not specify when to use this tool over alternatives like invoice_ocr or invoice_tables. There is no explicit guidance on prerequisites or when not to use it, leaving the agent to infer usage from the field list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
invoice_from_urlBInspect
Download PDF from URL and run complete invoice analysis.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | Public URL to PDF invoice e.g. 'https://example.com/invoice.pdf' |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full responsibility for behavioral disclosure. It only states the action without revealing side effects, error handling, or what 'complete invoice analysis' entails. Lack of transparency about destructive or read-only nature.
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 sentence that is concise but omits necessary details. It is front-loaded, but brevity compromises completeness.
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?
Given the tool fetches external content and performs analysis, the description lacks information about output format, behavior on invalid URLs, or any error conditions. No output schema exists, so more context is needed.
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 coverage is 100% with a clear parameter description. The tool description adds no new information beyond the schema's description of the 'url' parameter, so baseline 3 is appropriate.
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 ('Download PDF from URL') and the objective ('run complete invoice analysis'), distinguishing it from sibling tools that handle specific invoice processing steps. The verb+resource+scope is specific.
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 on when to use this tool versus alternatives like invoice_ocr or invoice_extract. The description does not mention when not to use it or any prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
invoice_ocrAInspect
OCR extraction for scanned or image-based PDF invoices using Tesseract (German + English).
| Name | Required | Description | Default |
|---|---|---|---|
| pdf_path | No | Server-side file path to PDF (alternative to base64) | |
| pdf_base64 | No | Base64-encoded PDF content |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It discloses the use of Tesseract and languages but does not state that the operation is read-only, what authentication is needed, or potential error behaviors. The description is adequate but lacks explicit non-destructive assurance.
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?
Single sentence of 12 words, front-loaded with key information (OCR extraction, target files, engine, languages). No unnecessary words; every part earns its place.
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?
Given the tool has two parameters, no output schema, and no annotations, the description covers the core functionality. However, it does not mention the return format or output, which could be useful for an agent. Still, for a straightforward OCR tool, it is nearly complete.
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 already explains both parameters (pdf_path and pdf_base64). The description adds context about the tool's OCR purpose but does not provide additional meaning beyond the schema for the parameters.
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?
Description clearly states the tool performs OCR extraction for scanned or image-based PDF invoices using Tesseract with German and English language support. This distinguishes it from siblings like invoice_parse_text (likely for text PDFs) and invoice_extract.
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 description implies usage for scanned/image-based PDFs but does not explicitly state when to use this tool versus alternatives like invoice_parse_text for text-based PDFs or invoice_extract for structured extraction. No exclusions or alternative suggestions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
invoice_parse_textAInspect
Extract all text from a PDF invoice. Returns text per page and full combined text.
| Name | Required | Description | Default |
|---|---|---|---|
| pdf_path | No | Server-side file path to PDF (alternative to base64) | |
| pdf_base64 | No | Base64-encoded PDF content |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses the output behavior (text per page and combined) but omits potential limitations, such as compatibility with scanned PDFs or error conditions. Adequate but not comprehensive.
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?
Two sentences, no unnecessary words. The description is optimally concise and front-loaded with the core functionality.
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?
Given no output schema, the description describes the return format. However, it could mention that it only works on text-based PDFs (not scanned images) to fully contextualize its use among siblings.
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%, and the description does not add extra meaning beyond the schema's parameter descriptions. Baseline score of 3 applies.
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 tool extracts text from a PDF invoice and specifies the return format (text per page and combined). This distinguishes it from sibling tools like invoice_ocr or invoice_extract.
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 description does not provide explicit guidance on when to use this tool versus alternatives, such as invoice_ocr for scanned PDFs or invoice_extract for structured data. Only implied context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
invoice_summaryAInspect
Complete invoice analysis in one call: all extracted fields, line items, ZUGFeRD check, and §14 UStG validation.
| Name | Required | Description | Default |
|---|---|---|---|
| pdf_path | No | Server-side file path to PDF (alternative to base64) | |
| pdf_base64 | No | Base64-encoded PDF content |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the full burden. It lists the outputs (fields, line items, checks, validation) but does not disclose behavioral traits such as side effects (read-only vs write), permissions, or rate limits. The tool name and context suggest it is a read-only analysis, but this is not explicitly stated.
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?
A single, well-structured sentence that front-loads the core purpose and lists the key components. Every phrase adds value, with no redundancy or filler. The colon organizes the information effectively.
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?
Given the complexity (multiple analysis types) and no output schema, the description adequately outlines the scope: extracted fields, line items, ZUGFeRD check, UStG validation. It misses details on output format or error handling, but for a summary tool, the overview is sufficient.
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% with clear parameter descriptions ('Server-side file path to PDF (alternative to base64)' and 'Base64-encoded PDF content'). The description adds no additional meaning beyond what the schema already provides, so baseline 3 is appropriate.
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 uses specific verbs and nouns: 'complete invoice analysis', 'all extracted fields, line items, ZUGFeRD check, and §14 UStG validation.' It clearly distinguishes from sibling tools like invoice_extract (partial extraction) or invoice_validate (validation only).
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 description implies this is the comprehensive option ('in one call'), but does not explicitly state when to use it versus alternatives. It lacks when-not-to-use guidance or comparisons to sibling tools, leaving the agent to infer the context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
invoice_tablesBInspect
Extract tables and line items (Positionen) from invoice. Returns structured rows with description, quantity, unit price, total.
| Name | Required | Description | Default |
|---|---|---|---|
| pdf_path | No | Server-side file path to PDF (alternative to base64) | |
| pdf_base64 | No | Base64-encoded PDF content |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description only states extraction and return type. Does not disclose auth needs, side effects, rate limits, or error handling. Bare minimum.
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?
Single sentence, no fluff. Could be slightly more structured (e.g., separate input constraints) but acceptable.
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?
Output described with fields, but no output schema. Lacks details on data format, multiplicity, error behavior. With no annotations, more completeness would help.
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 coverage is 100% with clear descriptions for pdf_path and pdf_base64. Description adds no additional parameter meaning beyond what schema provides.
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?
Clearly states it extracts tables/line items from invoices with specific fields (description, quantity, unit price, total). Distinguishes from siblings like invoice_summary or invoice_extract by focusing on structured line items.
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 on when to use this tool vs alternatives (e.g., invoice_extract, invoice_ocr). No mention of prerequisites or preferred input method.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
invoice_validateBInspect
Validate invoice against German §14 UStG legal requirements. Returns compliance score and list of missing mandatory fields.
| Name | Required | Description | Default |
|---|---|---|---|
| pdf_path | No | Server-side file path to PDF (alternative to base64) | |
| pdf_base64 | No | Base64-encoded PDF content |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. It states validation against German law and output format, but omits side effects (e.g., file deletion), error handling, authentication needs, or rate limits. This is insufficient for a validation tool.
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, focused sentence that efficiently conveys the tool's purpose and output. No extraneous information.
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?
While the output (compliance score, missing fields) is mentioned, there is no explanation of error scenarios, prerequisites (e.g., invoice must be readable), or limitations (e.g., only German invoices). Given the complexity of validation and no output schema, more context would help.
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 covers both parameters with clear descriptions (pdf_path and pdf_base64). The description adds no extra meaning beyond the schema, so the baseline score of 3 applies.
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 explicitly states the tool validates invoices against German §14 UStG legal requirements and returns a compliance score and missing fields. This clearly distinguishes it from sibling tools like invoice_extract or invoice_summary.
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 on when to use this tool versus alternatives (e.g., invoice_parse_text, invoice_zugferd). It also doesn't mention prerequisites, such as needing to have the invoice data already extracted, or how to choose between pdf_path and pdf_base64.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
invoice_zugferdAInspect
Parse ZUGFeRD or XRechnung XML data embedded in PDF. Returns structured invoice data from machine-readable format.
| Name | Required | Description | Default |
|---|---|---|---|
| pdf_path | No | Server-side file path to PDF (alternative to base64) | |
| pdf_base64 | No | Base64-encoded PDF content |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It indicates a read operation (parse, returns data) but does not disclose potential edge cases, permission requirements, or behavior on invalid input. It is adequate but lacks behavioral richness.
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 sentence (12 words) that conveys the core functionality. It is front-loaded with the key action and resource, with no extraneous information.
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?
No output schema is provided, and the description only states 'returns structured invoice data' without specifying the structure or fields. Given the complexity of invoice data and the presence of sibling tools that likely return summaries or different formats, this is insufficient for the agent to understand the output.
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?
Since the input schema already fully describes both parameters (pdf_path and pdf_base64) with clear descriptions, the description adds no additional meaning beyond what the schema provides, matching the baseline for 100% coverage.
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 specific action (parse) and resource (ZUGFeRD/XRechnung XML in PDF). It distinguishes itself from sibling tools like invoice_ocr or invoice_parse_text by targeting machine-readable embedded XML formats.
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?
Usage is implied for PDFs containing ZUGFeRD or XRechnung data, but there is no explicit guidance on when not to use it (e.g., for image-based invoices) or mention of alternatives like invoice_parse_text for text-based invoices.
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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