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Bulk Update Records

servicenow_bulk_update

Update multiple ServiceNow records matching a query. Preview changes with dry-run before committing to avoid errors.

Instructions

Update multiple records matching a query. Dry-run by default — always preview before committing.

Args:

  • table (string): Target table (e.g., incident, change_request)

  • query (string): Encoded query to select records (e.g., 'state=6^resolved_atRELATIVELT@dayofweek@ago@30')

  • data (object): Fields to set on all matched records

  • dry_run (boolean): Preview without applying (default: true). Set false to commit.

  • limit (number): Safety cap — max records to process (default 20, max 100)

  • response_format: Output format

Returns: Preview list (dry_run=true) or per-record success/failure results

Examples:

  • Close all resolved incidents older than 30 days → table="incident", query="state=6^resolved_atRELATIVELT@dayofweek@ago@30", data={"state":"7"}

  • Reassign open tickets to a new group → table="incident", query="assignment_group=OLD_SYS_ID^state!=7", data={"assignment_group":"NEW_SYS_ID"}

  • Set category on unclassified incidents → table="incident", query="category=^state=1", data={"category":"software"}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesFields to set on all matching records
limitNoMaximum number of results to return (1–100, default 20)
queryNoEncoded ServiceNow query string (e.g., 'state=1^priority=1^assigned_to=javascript:gs.getUserID()'). Leave empty to return all records.
tableYesServiceNow table name (e.g., incident, change_request, sys_user)
dry_runNoPreview without applying — set false to commit (default: true)
response_formatNoOutput format: 'markdown' (default) for human-readable or 'json' for structured datamarkdown
Behavior5/5

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

Annotations provide readOnlyHint=false and destructiveHint=false, but the description adds critical behavioral detail: the dry-run default, the safety cap via 'limit', and the return behavior ('Preview list (dry_run=true) or per-record success/failure results'). This goes beyond annotations by explaining the commit process and safeguards, which is essential for a bulk mutation tool.

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 well-organized with a one-sentence summary, an Args list, Returns, and Examples. It is front-loaded with the key safety warning. However, the Args list largely duplicates schema descriptions, though the examples add value.

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?

The description covers the tool's purpose, key parameters, safety features, and output behavior. It includes three practical examples that illustrate common use cases. Since there is no output schema, the Returns line is essential and provided. This is comprehensive for a bulk update tool.

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?

The input schema already describes all six parameters with 100% coverage. The description repeats them but adds context: 'limit' is described as a 'Safety cap — max records to process' rather than just a maximum results count, and examples show realistic encoded queries for 'query' and usage patterns for 'data'. The Returns line clarifies what different parameter values produce.

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 a specific verb and resource: 'Update multiple records matching a query.' This clearly distinguishes it from sibling tools like servicenow_update_record (single record) and servicenow_bulk_delete (delete). The title 'Bulk Update Records' reinforces the scope.

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 clearly states the tool is for updating multiple records matching a query, implying bulk operations. It provides safety guidance: 'Dry-run by default — always preview before committing.' However, it doesn't explicitly name alternatives like servicenow_update_record for single-record updates, so exclusions are implicit rather than explicit.

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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