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update_ai_booking_rule

Read/merge/edit a rule without losing its cost center or other unedited fields. Default preview; preserves existing automation but never enables it.

Input Schema

NameRequiredDescriptionDefault
kindYes
changesYes
dry_runNo
rule_idYes
company_nameNo
operation_keyNo
expected_revisionNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior4/5

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

With zero annotations the description carries the full burden and does add real behavioral context: it merges rather than replaces (preserving cost center and unedited fields), it defaults to a non-committing preview, and it will not silently enable automation. What it omits is the concurrency/permission story implied by expected_revision and operation_key, and what a failed merge looks like.

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?

Two tight sentences with the merge guarantee front-loaded and no filler. The compound 'Read/merge/edit' is slightly hedged phrasing, but nothing is wasted.

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

Completeness2/5

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

For a 7-parameter mutation with a nested object, no annotations, and no schema descriptions, the description is too thin — an output schema covers return values, but the agent still cannot tell what 'kind' accepts, how expected_revision interacts with the write, or what operation_key is for.

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

Parameters2/5

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

Schema description coverage is 0% across 7 parameters (including a free-form nested 'changes' object), so the description must compensate. It only obliquely touches dry_run ('Default preview') and the preservation semantics relevant to 'changes'; kind, rule_id, company_name, expected_revision, and operation_key are never mentioned, leaving the agent to guess at revision-conflict and idempotency behavior.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The verb set ('Read/merge/edit') and the merge-not-replace semantic are specific enough that an agent knows this is a partial-update tool rather than a create/delete. However, it says 'a rule' rather than 'an AI booking rule', so the resource is only identified by the tool name, and differentiation from update_bank_transaction_booking_rule / update_accounting_booking_rule comes from the name alone.

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

Usage Guidelines3/5

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

'Default preview' implies the intended preview-then-apply workflow and hints that dry_run must be turned off to commit, which is useful implied guidance. But there is no explicit statement of when to use this versus create_ai_booking_rule, clone_ai_booking_rule, plan_ai_booking_rule_batch, or the activation tools (set_ai_booking_rule_auto_booking / explicit_enable_bank_rule_auto_booking), and no prerequisites or conflict-handling advice.

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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