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Scheduled employer contribution changes

scheduled_changes
Read-only

Use this when the user asks what is changing in a country's statutory employer contributions: new rates, ceilings, floors or thresholds, their effective dates, or measures announced in a budget (e.g. "employer contribution changes in Ireland in 2027", "hausse des cotisations patronales en Allemagne l'an prochain"). Each change comes with its status (enacted, or announced in a budget and not yet enacted), whether the date is stated in the source or deduced from it, and the source with a word-for-word quote and its reading date. A country whose changes are not tracked yet is answered "not yet tracked", which does not mean that nothing is scheduled. Data snapshot 2026-10-22. Cost comparison, not legal or tax advice.

Input Schema

NameRequiredDescriptionDefault
countryYesISO 3166-1 alpha-2 code ("DE") or country name ("Germany")

Output Schema

NameRequiredDescriptionDefault
metaYes
changesYes
countryYes
pendingYes
readingYes
summaryYes
coverageNo
trackingYes
researched_onNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Goes well beyond readOnlyHint: it discloses that each change carries a status (enacted vs announced), whether the date is stated or deduced, and a word-for-word source quote with reading date. It also warns that 'not yet tracked' does not mean nothing is scheduled, and pins the data snapshot date — exactly the kind of epistemic caveats an agent needs to avoid overstating results.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads the trigger condition before the return semantics, and every clause (status, deduced dates, quotes, snapshot date, disclaimer) carries information. It runs long and bundles the disclaimer into the same sentence as the data snapshot, but nothing is filler.

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?

An output schema exists, yet the description still summarizes the meaningful payload (status, date provenance, source quote) so the agent knows what it is getting. With one fully-documented parameter and annotations covering safety, nothing needed 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% (ISO alpha-2 or country name), so the parameter is already fully documented. The description only refers to 'a country's' contributions and adds no format, ambiguity, or edge-case guidance beyond the schema, so baseline 3 applies.

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?

States a specific verb and resource: retrieving scheduled statutory employer contribution changes (rates, ceilings, floors, thresholds, effective dates, budget announcements). None of the siblings (compare_countries, cost_next_year, employer_cost) cover forward-looking statutory change tracking, so the boundary is implicit but unmistakable.

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?

Opens with an explicit trigger ('use this when the user asks what is changing...') and gives concrete multilingual query examples that make the intended intent recognition unambiguous. It stops short of naming which sibling to use instead for current-year rates or cost comparison, so the negative case is only covered by the 'cost comparison, not legal or tax advice' caveat.

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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