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update_mr_note

Edit the body of an existing merge request note using its global ID. Supports a dry-run mode to preview changes before applying.

Instructions

Edit the body of an existing MR note. Get note_id from list_mr_notes. dry_run=true by default.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
note_idYesNote global ID (e.g. gid://gitlab/Note/123 or gid://gitlab/DiscussionNote/123). Returned by list_mr_notes.
bodyYesNew note body (Markdown). Replaces the existing content entirely.
dry_runNoDry run mode (default: true). When true, returns a preview of the action without executing it. Set to false only after user confirmation.
Behavior3/5

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

Annotations only state readOnlyHint=false, indicating a write operation, which aligns with the description. The description adds behavioral context: 'dry_run=true by default' reveals the default preview behavior. However, it does not disclose the return value or side effects after an actual update (e.g., whether it returns the updated note or a success message), which is a gap given no output schema.

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 extremely concise with three short sentences: one for purpose, one for prerequisite, one for default behavior. Every sentence is necessary and adds distinct value without any fluff. It is front-loaded with the core action.

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?

Given the simple tool (3 params, no output schema), the description covers the core purpose, required note_id source, and dry_run default. However, it lacks information about the return value or confirmation after a real update, which an agent might need to verify success. The prerequisite hint and default behavior make it reasonably complete but not fully comprehensive.

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

Parameters3/5

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

Schema description coverage is 100%, so the baseline is 3. The description adds value by explaining note_id's source ('Get note_id from list_mr_notes') and dry_run's default, but these are already implied in the schema descriptions. It does not add significant new meaning beyond what is in the schema, keeping the score at baseline.

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 clearly states 'Edit the body of an existing MR note,' specifying the verb (edit) and resource (body of MR note). This distinguishes it from sibling tools like add_mr_note (create) and delete_mr_note (delete), and from similar update tools for other entities (e.g., update_issue_note). The mention of dry_run further clarifies 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?

The description provides a key prerequisite: 'Get note_id from list_mr_notes,' guiding the agent on sourcing the required ID. It also highlights the default dry_run mode, instructing the agent to use it for previews before actual execution. However, it does not explicitly mention when not to use this tool or alternatives like update_issue_note, though the resource specificity mitigates this.

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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