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apply_stage_batch

Apply up to 100 layer, arc, variant, semantic, or attribute edits atomically. Preview changes first, and any failed operation restores the stage snapshot for safe batch updates.

Instructions

Preview or atomically apply up to 100 layer/arc/variant/semantic/attribute edits. Any failed operation restores the stage snapshot.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
previewNo
command_idNo
operationsYes
idempotency_keyNo
readback_root_pathNo/

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Install Server

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden and does a good job: it discloses atomicity, failure rollback ('any failed operation restores the stage snapshot'), and the preview/apply dual mode. It does not mention permission requirements or side effects beyond the stated atomic transaction, but the key failure semantics are clearly provided.

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 two sentences with no filler. The primary capability is front-loaded, the batch limit is stated, and the most important behavioral guarantee (atomic rollback) is included. Every sentence earns its place.

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 complex batch mutation tool with no annotations and 0% schema coverage, this is not complete enough. The description conveys the broad contract but leaves the agent unable to correctly construct 'operations' objects or understand the auxiliary parameters. While an output schema exists, the input semantics are too underspecified for reliable autonomous invocation.

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%, so the description must compensate for the opaque schema. It broadly characterizes the operations as layer/arc/variant/semantic/attribute edits, but it does not explain the structure of each operation object, the meaning of preview, command_id, idempotency_key, or readback_root_path. The additionalProperties: true schema leaves these critically under-specified.

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 states a specific verb ('apply' or 'preview'), a clear resource ('stage batch'), a capacity (up to 100 edits), and the kinds of edits covered ('layer/arc/variant/semantic/attribute'). This clearly distinguishes it from the many single-edit siblings like edit_sublayer and set_variant_selection.

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?

The description implies batch usage by mentioning 'up to 100' edits and atomic apply, but it never explicitly says when to choose this tool over calling individual edit tools. It also hints at a preview-then-apply workflow without spelling it out as a recommended sequence.

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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