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finance

Transactions: Update transaction

update_transaction
    Update an existing transaction.

    Args:
        transaction_id: The ID of the transaction to update
        description: New description (optional)
        amount: New amount as positive number (optional, will adjust account balance)
        category_name: New category name, case-insensitive (optional)
        transaction_date: New date in YYYY-MM-DD format (optional)
        tag_names: List of tag names to assign (optional, replaces existing tags)

    Returns:
        Updated transaction details with new account balance
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
amountNo
tag_namesNo
descriptionNo
category_nameNo
transaction_idYes
transaction_dateNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations only provide basic hints (readOnlyHint=false, destructiveHint=false). The description adds meaningful behavioral context by stating that setting amount 'will adjust account balance' and that tag_names 'replaces existing tags'. These side effects go beyond what the annotations convey and are critical for an agent to anticipate the consequences of a call.

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?

The description is well-structured: a one-line purpose, a bulleted Args list, and a Returns line. Every sentence earns its place, with the most important information (the action) front-loaded and parameter details concisely formatted. No filler or redundancy.

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?

Despite having no output schema, the description clearly explains the return value ('Updated transaction details with new account balance'). It covers all six parameters, their constraints, and side effects. While it doesn't mention error conditions or prerequisites like 'transaction must exist', these are common for update tools and the given context is sufficient for correct invocation.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must carry all parameter meaning. It does so thoroughly: amount is 'positive number', category_name is 'case-insensitive', transaction_date has an explicit 'YYYY-MM-DD' format, and tag_names explicitly replaces existing tags. This is exactly the type of semantic enrichment the schema lacks.

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 'Update an existing transaction', a specific verb and resource that clearly distinguishes it from other update_* tools for accounts, budgets, categories, etc. The list of updatable fields reinforces the scope. No ambiguity about which entity is affected.

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

Usage Guidelines2/5

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

There is no explicit guidance about when to use this tool versus alternatives like recategorize_similar_transactions, bulk_categorize_transactions, or undo_transaction. The description simply states what it does without providing context on the appropriate conditions or excluding cases. This leaves the agent to infer usage from the tool name alone.

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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