Skip to main content
Glama

openfinance_update_transaction_category

Corrects the category of one or more transactions (PATCH /transactions/:id). Pass items as an array of { transaction_id, category_id } — transaction_id comes from openfinance_list_transactions, category_id from openfinance_list_categories. This overrides Pluggy's automatic categorization AND teaches Pluggy: recategorizing a transaction automatically creates a Category Rule for this client (case-insensitive exact match on the transaction's data), so FUTURE similar transactions are categorized the same way — use this to fix miscategorized transactions and improve categorization accuracy going forward. Batch shape: returns { updated, results: [{ transaction_id, category, categoryId }], errors: [{ id, status, message }] } — per-item errors do not fail the whole batch.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYes

Schema Changelog

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

  1. Added
  2. Removed
  3. Added
  4. Removed
  5. Added
  6. Removed
  7. First observed

TDQS

A4.5/5.0
Behavior5/5

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

The description discloses key behavioral traits beyond annotations: the operation overrides automatic categorization and creates a Category Rule that affects future similar transactions, and outlines batch error handling (per-item errors don't fail the batch). This is critical for an AI agent to understand side effects.

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 description is front-loaded with the action and endpoint, then details parameters, side effects, and response shape. It is somewhat lengthy but every sentence adds value. Could be slightly tightened.

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?

The description covers the endpoint, required fields, ID sources, side effects, and response structure. It does not mention authentication or error codes, but given the complexity and absence of output schema, it provides sufficient context for an AI agent to use the tool effectively.

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?

With schema description coverage at 0%, the description adds necessary meaning by explaining each field (transaction_id, category_id) and their origins. It lacks explicit types or constraints, but provides enough context for correct invocation.

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 starts with 'Corrects the category of one or more transactions (PATCH /transactions/:id),' using a specific verb and resource. It clearly distinguishes from sibling listing tools like openfinance_list_transactions and openfinance_list_categories.

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?

It instructs to pass items as an array with transaction_id and category_id sourced from specific sibling tools, and explains the side effect of creating a Category Rule. While it doesn't explicitly state when not to use it, the context implies fixing miscategorized transactions. Slight room for more explicit exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.