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YESbusiness

by ch.yesbusiness
OverviewDiscussionsAdmin

Bookkeeping guide

get_bookkeeping_guide
Read-onlyIdempotent

The Swiss bookkeeping conventions this company's books follow, as text to read before interpreting figures or preparing a booking: account numbering and types, what a draft is and the booking rules, VAT codes, rates and methods, and the money rules (integer cents, home currency, sign conventions). It also returns the company's own settings the conventions depend on: home currency, activated foreign currencies, accounting years with status and exchange-rate method, and whether the company is VAT-registered. Static per company; call it once per conversation, not per question. Choose a topic to get one section, or omit it for all four.

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": {
      "company_id": "<company_id>"
    },
    "name": "get_bookkeeping_guide"
  }
}

Input Schema

NameRequiredDescriptionDefault
topicNoOne section, or 'all' (default).
company_idYesThe company to work on — one of list_my_companies' company_id values.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already cover safety (readOnly, idempotent, non-destructive, closed-world), and the description adds genuinely new behavior: the content is static per company, so repeated calls are wasteful, and it discloses the returned payload categories including company settings the conventions depend on. It stops short of describing the exact response shape or how sections are delimited, which keeps it below a 5.

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?

The purpose and the pre-interpretation use case are front-loaded, and the enumeration of sections earns its length by telling the agent what the text covers. It is a single dense paragraph, though, and the returned-settings clause could be tighter.

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

Completeness4/5

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

With no output schema, the description carries the burden of explaining returns, and it does so by listing content areas and the settings block. It is sufficient for an agent to decide to call it and to pick a topic, with only the precise response format left unspecified.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning: it defines the four section topics that the enum values correspond to and clarifies that omitting the topic yields all four, matching the 'all' default. The company_id scoping is implied by 'this company's books' rather than restated.

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 names a specific resource (the company's Swiss bookkeeping conventions) and enumerates exactly what it contains: account numbering/types, draft and booking rules, VAT codes/rates/methods, and money rules. It also states the secondary payload (company settings such as home currency, accounting years, VAT registration), so an agent can distinguish this reference-text tool from data-returning siblings like list_accounts or list_vat_codes.

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?

It explicitly frames the when-to-use: read before interpreting figures or preparing a booking, and it adds a frequent-mistake guard ('call it once per conversation, not per question'). It also explains how to narrow scope via the topic parameter versus omitting it for all four sections.

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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