Screen 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.
Add one secure layer between your agents and this server.
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.
