Group journal entries with identical date, amount, debit, and credit accounts to reveal potential duplicates.
計上日・金額・借方科目・貸方科目が完全に一致する仕訳をグループにして返す。
| Name | Required | Description | Default |
|---|---|---|---|
| journals | Yes | 仕訳の配列。簡易形 { date, debit_account, credit_account, amount } か、明細形 { date, lines: [{ account, debit, credit }] } のどちらでも受ける。 |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the grouping behavior (returns groups of matching journals) and the exact matching criteria. However, it doesn't disclose what the output format looks like, whether it handles both simple and detailed journal forms consistently, or any edge cases like partial matches or how groups are ordered.
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?
The description is a single, focused sentence in Japanese that states the core behavior and matching criteria. It's efficient and front-loaded with the key information. It could arguably add a note about output format, but as-is it's concise and clear.
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?
For a tool with one parameter and no output schema, the description covers the input format and matching logic. However, it doesn't describe the return value structure (what a 'group' looks like), which is important for an agent to use the result. Given the tool's simplicity, this is a moderate gap.
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 description coverage is 100%, so the schema already documents the journals parameter thoroughly, including both simple and detailed forms. The description adds the matching criteria context but doesn't add new parameter-level meaning beyond what the schema provides. Baseline 3 is appropriate.
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 states a specific verb ('detect duplicates'), a resource ('journals'), and the exact matching criteria (date, amount, debit account, credit account all matching). It clearly distinguishes this from sibling tools like benford_analysis or check_balance, though it doesn't explicitly name them.
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 implies when to use this tool: when you need to find journal entries that are exact duplicates across four fields. However, it doesn't explicitly state when not to use it or mention alternatives like screen_journals for reviewing entries. The usage context is clear but not fully elaborated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.