toolforte

UPA File Generator

generate_upa_files

Read-onlyIdempotent

Generate UPA pension declaration XML (the Dutch payroll-to-pension-fund message) for one or more periods, with employments, schemes and optional deliberate defects that a receiving system should reject. Deterministic per seed. XML is large, so ask for the summary format unless you need the file contents; for bulk use the REST API at https://toolforte.com/api/v1/tools/upa-file-generator

Input Schema

TableJSON Schema

Name	Required	Description	Default
`seed`	No	Same seed returns the same employments. Omit for the default set.
`count`	No	Employments to generate.
`format`	No	summary returns file names and warnings only, which is usually what you want. xml returns full file contents and can be very large.	summary
`months`	No	How many monthly periods to generate, 1 to 12 (default 1)
`defects`	No	Switch on deliberate defects to test rejection paths. Valid ids: invalidBsn, duplicateBsn, duplicateNumIv, totalsMismatch, endBeforeStart, dateOutsidePeriod, unknownRegVrnt, negativeAmount, zeroNormHours, missingMandatory
`startYear`	No	Year of the first period
`schemeType`	No	Pension scheme type: FPR, SPR or DB
`startMonth`	No	Month of the first period, 1 to 12

Output Schema

TableJSON Schema

Name	Required	Description
`seed`	No
`format`	No
`result`	No	The result, when it is not an object
`fileCount`	No
`fileNames`	No
`peopleCount`	No

Schema Changelog

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

Changed6 schema fields changedSep 5, 2026

addedInput schema / properties / months / description

Added value: +"How many monthly periods to generate, 1 to 12 (default 1)"

addedInput schema / properties / schemeType / description
```
Added value: +"Pension scheme type: FPR, SPR or DB"
```

addedInput schema / properties / seed / description

Added value: +"Same seed returns the same employments. Omit for the default set."

addedInput schema / properties / startMonth / description
```
Added value: +"Month of the first period, 1 to 12"
```
addedInput schema / properties / startYear / description
```
Added value: +"Year of the first period"
```

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "additionalProperties": {},
+  "properties": {
+    "fileCount": {
+      "type": "number"
+    },
+    "fileNames": {
+      "items": {},
+      "type": "array"
+    },
+    "format": {
+      "type": "string"
+    },
+    "peopleCount": {
+      "type": "number"
+    },
+    "result": {
+      "description": "The result, when it is not an object"
+    },
+    "seed": {
+      "type": "number"
+    }
+  },
+  "type": "object"
+}

First observedSep 1, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Discloses behavioral traits beyond annotations: 'Deterministic per seed' (reproducibility), 'XML is large' (output size warning), and the bulk API suggestion. Annotations already provide safety hints, and the description adds practical runtime context without contradicting them.

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?

Two sentences carry the core purpose, determinism, output-size caveat, and bulk alternative without wasted words. The most critical information (what it generates) is front-loaded.

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?

For a tool with 8 parameters and nested objects, the description captures the essential choices (periods, schemes, defects), important caveats (large XML, summary vs full), and routing guidance (REST API for bulk). Since an output schema exists, describing return values is unnecessary.

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 description coverage is 100%, so all 8 parameters (seed, count, format, months, defects, startYear, schemeType, startMonth) are well documented in the schema. The description only echoes 'one or more periods' and 'defects', adding no meaningful new parameter meaning. Baseline 3 per the high-coverage rule.

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 states a specific verb ('Generate'), resource ('UPA pension declaration XML'), and scope ('for one or more periods, with employments, schemes and optional deliberate defects'). It clearly distinguishes this from other generate_* tools by naming the exact Dutch payroll-to-pension-fund message and its purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit when-to-use guidance: 'ask for the summary format unless you need the file contents' and 'for bulk use the REST API'. This tells the agent exactly when to prefer a lighter output or an alternative endpoint, which is valuable for correct invocation.

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

A3.8/5.0

Disambiguation5/5

Every tool targets a distinct resource or action, and the detailed descriptions clearly separate near neighbors like generate_test_bsn versus generate_brp_test_data, read_page versus url_screenshot versus url_to_pdf, and image_compress/convert/resize. Even with 40 tools, there is no real boundary-blurring overlap.

Naming Consistency3/5

All names are snake_case and readable, but the set mixes conventions: verb_noun (generate_*, validate_*), noun_verb (pdf_merge, image_resize), conversion-style names (csv_to_json, html_to_pdf), and bare nouns (base64, qr_code_png). The groups are recognizable, but there is no single predictable pattern.

Tool Count2/5

Forty tools is an oversized surface for an agent to consider on every call, well above the point where tool selection cost starts to hurt. The broad purpose explains the count, but many one-off utilities could be grouped or exposed selectively.

Completeness3/5

The server covers many domains—encoding, Dutch test data, image/PDF handling, memory, and workflows—but several categories are partial: there are no reverse conversions like json_to_csv or html_to_markdown, no PDF text extraction, and no workflow create/update/delete tools. Agents can work around some gaps, but notable operations are missing.

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