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cubicecho

MCP Actual

by cubicecho

Apply rule actions to transactions

apply_rule_actions
Destructive

Bulk-edit transactions by applying rule actions to specific transaction IDs and saving changes; use IDs from preview_rule_effects. Up to 500 per call.

Instructions

Apply rule actions to specific transactions and SAVE the result. This is the write half of preview_rule_effects: preview first, then pass the transaction ids it returned. The actions are applied UNCONDITIONALLY to every id you pass — rule conditions are NOT evaluated here, so a wrong id is silently changed rather than skipped. Pass only ids you have actually seen, from preview_rule_effects or search_transactions; never ids you assembled yourself. Edits real transactions in bulk, at most 500 per call, and cannot be undone through this server. Actions use the same format as create_rule (see describe_rule_schema), and values are ids, not names — preview_rule_effects reports these as toId. Returns the ids actually updated, plus any that did not exist under missing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionsYesActions to apply. Same format as create_rule.
transactionIdsYesIds of the transactions to change. At most 500.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare destructive/non-idempotent/openWorld, but the description adds substantial context beyond them: actions are applied UNCONDITIONALLY with no condition evaluation, wrong ids are silently changed rather than skipped, edits are bulk-capped at 500 per call, changes cannot be undone via this server, and values are ids not names. This is exactly the extra behavioral detail annotations cannot express.

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 write-vs-preview relationship and the 'SAVE' behavior are front-loaded, and each subsequent sentence adds a distinct operational fact. It is dense and runs a bit long, but almost no sentence is redundant; minor trimming possible without loss.

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?

No output schema exists, yet the description explains the return payload (updated ids plus a 'missing' list for ids that did not exist), and covers the write semantics, limits, reversibility, and id provenance an agent needs to call this safely.

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 clarifies that action values are ids rather than names (reported as toId by the preview), that actions share create_rule's format (pointing to describe_rule_schema), and restates the 500 cap. This compensates for the enum-heavy action object being otherwise opaque.

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+resource ('apply rule actions to transactions and SAVE') and positions itself precisely as 'the write half of preview_rule_effects', which immediately distinguishes it from the preview sibling. An agent knows exactly what this does and how it relates to the read-only counterpart.

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?

Explicit sequencing ('preview first, then pass the transaction ids it returned'), explicit source constraint (only ids from preview_rule_effects or search_transactions, never self-assembled), and an explicit warning about unconditional application. When-to-use and when-not-to-use are both covered.

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