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Update pipeline schedule variable

update_pipeline_schedule_variable

Update an existing pipeline schedule variable in GitLab by specifying project, schedule ID, key, and new value. Modifies the variable without returning its current value.

Instructions

Update a pipeline schedule variable without returning its value.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYes
valueYes
projectYesGitLab project ID or full path such as group/project.
variable_typeNo
pipeline_schedule_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYesGitLab response normalized for model use.
Behavior3/5

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

Annotations indicate readOnlyHint=false, meaning this is a write operation, which the description implies with 'Update'. The description adds the note 'without returning its value,' which is useful behavioral context not in annotations. However, it does not disclose potential side effects (e.g., pipeline schedule being affected) or error conditions. No contradiction.

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 a single clear sentence that is efficient and front-loaded. No fluff. It could be slightly more informative but is appropriately concise.

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?

Despite having an output schema (which may clarify return), the description is minimal for a mutation tool with 5 parameters and no annotations beyond truth flags. It lacks important context like whether the variable must already exist, what 'value' formats are allowed, and how variable_type affects the operation. The output schema exists but doesn't compensate for the absence of usage guidance.

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 only 20% (only 'project' has a description). The description does not elaborate on any parameters, such as 'key', 'value', 'variable_type', or 'pipeline_schedule_id'. It leaves the agent to infer meaning from names alone. With low coverage, the description should compensate but does not.

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

Purpose3/5

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

The description 'Update a pipeline schedule variable without returning its value' clearly identifies the action and resource. It is a specific enough purpose, but it lacks detail beyond the verb and resource. It is not a tautology, but it does not distinguish from siblings like create_pipeline_schedule_variable or delete_pipeline_schedule_variable.

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

Usage Guidelines2/5

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

The description provides no context on when to use this tool vs alternatives. It does not mention that it is for existing variables or that it differs from create or delete. No exclusions or alternative tools are referenced.

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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