PDF tools + invoice extraction, bank statement parsing, GST reconciliation & GSTIN validation.
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Average 3.8/5 across 7 of 7 tools scored.
Each tool targets a distinct document processing task (compression, fraud detection, invoice extraction, statement parsing, conversion, reconciliation, GST validation) with clear descriptions that avoid overlap.
All tool names follow the verb_noun snake_case pattern (e.g., compress_pdf, validate_gstin), providing a predictable and uniform naming convention.
Seven tools cover the core capabilities for a PDF/document magic service focused on financial documents, balancing breadth without being overwhelming or sparse.
The set addresses key workflows (compress, convert, extract, parse, validate, reconcile), but misses general OCR or merge/split features. For the financial niche, it is nearly complete.
compress_pdfAInspectCompress a PDF file to reduce its size. Returns a download URL for the compressed file. Free tier: 500 calls/month.
| Name | Required | Description | Default |
|---|---|---|---|
| file_url | No | HTTPS URL of the file to process (the server downloads it) | |
| filename | Yes | Filename with extension, e.g. invoice.pdf | |
| file_base64 | No | Base64-encoded file content (alternative to file_url; max 15MB decoded) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral transparency burden. It adds that the tool returns a download URL and has a rate limit. However, it does not disclose file size limitations, whether the original file is modified, or URL expiration. This is incomplete but not misleading.
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 extremely concise: three sentences that front-load the core purpose, result, and a usage constraint. Every sentence adds value, with no verbosity.
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 3 parameters and no output schema, the description is adequate but incomplete. It does not clarify the relationship between file_url and file_base64 (they are alternatives) or specify the response format beyond a download URL. Additional context would improve completeness.
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 parameters are well documented. The tool description adds no additional meaning beyond the overall purpose. Baseline of 3 is appropriate as the description does not enhance parameter understanding beyond what the schema already 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 the tool compresses a PDF to reduce size and returns a download URL. It uses a specific verb 'compress' and resource 'PDF file'. It distinguishes from siblings like pdf_to_excel (conversion) and others, making the purpose unmistakable.
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 guidance on when to use this tool versus alternatives, such as pdf_to_excel or extract_invoice_data. It mentions a free tier limit (500 calls/month) but lacks explicit when-to-use or when-not-to-use context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
detect_document_fraudAInspectScreen a batch of 2+ invoices/documents for fraud signals: fabricated GSTINs (check-digit), duplicate invoice numbers across documents, duplicate/near-duplicate files, and amount anomalies. Requires Developer tier or above.
| Name | Required | Description | Default |
|---|---|---|---|
| files | Yes | 2-10 documents. Each item: {file_url OR file_base64, filename} |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description discloses key behaviors: it detects specific fraud signals (fabricated GSTINs via check-digit, duplicate invoice numbers, near-duplicate files, amount anomalies). It does not discuss data handling (e.g., temporary storage, deletion) or rate limits, but the listed signals provide adequate transparency for a screening 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?
Two sentences, no redundancy. The first sentence front-loads the purpose and specific checks; the second provides the access constraint. Every phrase 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 no output schema, the description lists detected signals, allowing the agent to infer the output structure. Sibling tools provide context. However, it does not describe the return format or error handling, which would improve completeness.
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%, so the baseline is 3. The description adds context ('batch of 2+ invoices/documents') and implies the file_url/file_base64 trade-off, but does not elaborate beyond the schema. The parameter description in the schema already covers the options.
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 specifies a clear verb ('Screen') and resource ('batch of 2+ invoices/documents'), lists specific fraud signals (fabricated GSTINs, duplicate invoice numbers, etc.), and distinguishes from sibling tools like validate_gstin (single GSTIN) and extract_invoice_data (extraction).
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 states the requirement ('Developer tier or above') and implies use for fraud detection. It does not explicitly state when not to use or suggest alternatives, but the context of sibling tools helps differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
extract_invoice_dataBInspectExtract structured data from an invoice PDF: vendor, invoice number, date, line items, taxes (GST-aware), totals — as JSON. Requires Team tier or above.
| Name | Required | Description | Default |
|---|---|---|---|
| file_url | No | HTTPS URL of the file to process (the server downloads it) | |
| filename | Yes | Filename with extension, e.g. invoice.pdf | |
| file_base64 | No | Base64-encoded file content (alternative to file_url; max 15MB decoded) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that file_url involves server download, and file_base64 has a 15MB limit. However, it does not mention error handling, file type validation, or whether the operation is read-only. The output format is mentioned but not detailed.
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 immediately states the purpose and output, followed by a necessary prerequisite. It avoids redundancy and is efficiently front-loaded.
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's complexity (extracting structured data from invoices) and the absence of an output schema, the description should elaborate on the return structure, field types, or example outputs. It only says 'as JSON' without any schema details, leaving ambiguity for the agent about what to expect.
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 has 100% description coverage, so the baseline is 3. The description does not add significant new meaning about parameters; it focuses on what the tool extracts rather than how the parameters are used. The parameter descriptions in the schema are already clear.
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 verb 'Extract' and the resource 'structured data from an invoice PDF', listing specific fields (vendor, invoice number, date, line items, GST-aware taxes, totals) and output format (JSON). It distinguishes from sibling tools like 'compress_pdf' and 'parse_bank_statement' by its specific focus on invoice extraction.
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 notes a prerequisite ('Requires Team tier or above') but provides no guidance on when to use this tool instead of similar alternatives like 'parse_bank_statement' or 'validate_gstin'. There is no mention of exclusions or typical scenarios, leaving the agent without clear decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
parse_bank_statementAInspectParse a bank statement PDF (any Indian bank + international formats) into categorized transactions with dates, amounts, balances, payment modes (UPI/NEFT/ATM/...), and an income/expense summary. Requires Developer tier or above.
| Name | Required | Description | Default |
|---|---|---|---|
| file_url | No | HTTPS URL of the file to process (the server downloads it) | |
| filename | Yes | Filename with extension, e.g. invoice.pdf | |
| file_base64 | No | Base64-encoded file content (alternative to file_url; max 15MB decoded) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description does not disclose processing time, error handling, file size limits (max 15MB only for base64), or supported formats beyond 'any Indian bank + international formats'. The behavior is only partially transparent.
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 concise sentence plus a requirement. It is front-loaded with essential information and contains no unnecessary words.
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 mentions return values (categorized transactions, summary) but lacks structure details (e.g., exact fields, categories). It also doesn't cover error cases or edge cases. Adequate but not thorough.
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 documents all parameters. The description adds context about the overall task but does not enhance parameter-specific meaning beyond what's in the schema.
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 verb (parse), resource (bank statement PDF), and specific outputs (categorized transactions, dates, amounts, balances, payment modes, income/expense summary). It distinguishes itself from sibling tools (none parse bank statements).
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 mentions the requirement (Developer tier or above) and implies use when parsing bank statements. However, it doesn't explicitly state when not to use or compare with alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pdf_to_excelBInspectConvert a PDF (tables, statements, reports) to an Excel file. Returns a download URL. Requires Premium tier or above.
| Name | Required | Description | Default |
|---|---|---|---|
| file_url | No | HTTPS URL of the file to process (the server downloads it) | |
| filename | Yes | Filename with extension, e.g. invoice.pdf | |
| file_base64 | No | Base64-encoded file content (alternative to file_url; max 15MB decoded) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose all behavioral traits. It mentions the Premium requirement and return of a download URL, but lacks details on processing limits, error handling, or potential side effects (e.g., file storage). This leaves the agent with incomplete understanding of 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 sentences, front-loaded with action, no unnecessary words. Every sentence adds value: what the tool does, what it returns, and a requirement.
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 3 parameters and no output schema, the description covers the output (download URL) and a requirement (Premium tier). However, it lacks details on file size limits, conversion accuracy, or failure modes. Adequate but not comprehensive.
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 each parameter described (file_url, filename, file_base64). The description adds no extra parameter semantics beyond the schema. Baseline score of 3 is appropriate as schema does the heavy lifting.
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 converts PDF to Excel, specifying types of PDFs (tables, statements, reports) and that it returns a download URL. This distinguishes it from sibling tools like compress_pdf or extract_invoice_data, which serve different purposes.
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?
Provides one usage constraint (requires Premium tier), but does not guide when to use this tool versus alternatives like extract_invoice_data or parse_bank_statement. No exclusions 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.
reconcile_documentsAInspectReconcile two or more documents (e.g. purchase register vs GSTR-2B, bank statement vs ledger). Matches line items by GSTIN + invoice number + amount; reports matches, mismatches with exact fields, and unmatched items. Requires Developer tier or above.
| Name | Required | Description | Default |
|---|---|---|---|
| files | Yes | 2-10 documents. Each item: {file_url OR file_base64, filename} |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses the matching behavior and a requirement (Developer tier), but does not mention if the operation is read-only, any rate limits, or the exact format of the output. The absence of such details leaves behavioral ambiguities.
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 three sentences, concise and to the point. It front-loads the main action and includes necessary context. Minor verbosity in the first sentence with examples does not detract significantly.
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 lack of annotations, output schema, and simple parameter structure, the description is relatively complete. It explains the matching logic and authorization requirement. It could be improved by specifying the output format or whether the tool is read-only, but it adequately covers the core functionality.
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?
With 100% schema description coverage, the schema already documents the 'files' parameter well. The description adds context about document types and matching logic but does not provide additional semantics for the parameter beyond the schema. Baseline score 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 reconciles two or more documents with specific examples (purchase register vs GSTR-2B, bank statement vs ledger) and details the matching logic (by GSTIN + invoice number + amount) and output (matches, mismatches, unmatched items). It distinguishes itself from sibling tools like extract_invoice_data or compress_pdf.
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 provides examples of when to use the tool (reconciling specific document pairs) and includes a tier requirement. However, it does not explicitly state when not to use it or mention alternative tools. The context is clear enough for an agent to infer appropriate scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_gstinAInspectValidate an Indian GSTIN: format and check-digit (base-36 checksum). Catches typos and fabricated numbers instantly. Runs locally — no API key required. Note: does NOT confirm active registration on the GST portal.
| Name | Required | Description | Default |
|---|---|---|---|
| gstin | Yes | 15-character GSTIN, e.g. 27AAPFU0939F1ZV |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, the description reveals important behaviors: local execution (no API required) and the limitation regarding active registration. This compensates for the lack of annotations.
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?
Three concise sentences (including a note) with no wasted words. The most critical information is front-loaded.
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 simple validation tool with one parameter, the description covers purpose, method, execution environment, and limitations. No additional context is needed given the lack of output schema or nested objects.
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 has 100% coverage with a clear description of the parameter. The description adds value by specifying the GSTIN length and providing an example, reinforcing the format expectations.
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 validates Indian GSTIN format and check-digit, distinguishing it from sibling tools that handle document processing. The verb 'validate' and resource 'Indian GSTIN' are specific and unambiguous.
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?
Explicitly notes the tool does NOT confirm active registration, guiding against misuse. It states runs locally with no API key, but does not mention alternative tools for active registration checks.
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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