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by OBrandon
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Payslip PDF to data

payslip
Read-onlyIdempotent

Extract structured payroll data from public salary statement PDFs, including employee/employer, pay period, gross, tax, deductions, net pay, and earnings/deduction lines.

Instructions

Read payslip PDFs at public URLs into structured data. Each item is one payslip: employee, employer, pay period and pay date, gross pay, tax, deductions, net pay, earnings lines (hours, rate, amount) and deduction lines, plus an Excel link. Text-based PDFs only, not scans. Cost: $5.00 per 1,000 payslips ($0.005 each) on the user's Apify account. Latency: usually 10-30 s.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "pdf_urls": "<pdf_urls>"
    },
    "name": "payslip"
  }
}

Input Schema

NameRequiredDescriptionDefault
pdf_urlsYesDirect public links to PDF files (https://...). The file must download without a login.
max_payslipsNoStop after this many payslips.
pdf_passwordNoOptional. Password for protected PDFs. Leave empty otherwise.
extract_linesNoAlso read earnings and deduction rows. Off = header fields and totals only.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.0

TDQS

A4.5/5.0
Behavior5/5

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

The description adds substantial context beyond the annotations: billing model ($0.005 per payslip on the user's Apify account), expected latency (10-30 s), and an input limitation (text-based PDFs only, not scans). Combined with readOnly/idempotent/openWorld hints, an agent knows the safety profile, cost, and turnaround before invoking.

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?

Five short sentences, front-loaded with purpose and record shape, followed by constraint, cost, and latency. Every sentence carries distinct operational information with no restatement of the name or title.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema covering return values and annotations covering safety, the description only needs to supply constraints, cost, and timing, all of which are present. Nothing an agent requires to call this correctly is missing.

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 coverage is 100%, so pdf_urls, max_payslips, pdf_password, and extract_lines are already documented in the schema. The description reinforces the accessibility constraint on the URLs ('must download without a login') but says nothing about the password parameter or how max_payslips interacts with the 20-URL limit, so it stays at baseline.

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 ('Read payslip PDFs at public URLs into structured data') and then enumerates the exact record shape (employee, employer, pay period, gross, tax, deductions, net, line items, Excel link). That specificity separates it from sibling document-extraction tools like invoice or bank_statement without requiring the schema to be opened.

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 gives clear operating context: inputs must be public, login-free, text-based PDFs and explicitly not scans, plus cost and latency expectations that help an agent decide whether to call it. It falls short of naming an alternative for the excluded case (scanned PDFs), so an agent must infer what to do instead.

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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