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lpenguin
by lpenguin

get_commands

Retrieve paginated command lists from a WebGPU capture, filtered by method or pass label, with index, arguments, and object details.

Instructions

Return a paginated, base64-stripped slice of a capture's command list. Each entry has its index, method, pass number, object, and arguments.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax entries to return (default 50, max 500).
methodNoOptional: only commands with this method name.
offsetNoStart index into the (filtered) list.
captureIdNoCapture id (default: most recent).
passLabelNoOptional regex: only commands inside a render/compute pass whose label matches.
Behavior4/5

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

With no annotations provided, the description carries the behavioral disclosure burden. It discloses two non-obvious behaviors: the result is paginated and base64 data is stripped. It also states the entry shape. It does not discuss mutability, but 'Return' implies a read operation and the description covers the most important behavioral traits.

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?

Two tight sentences with no filler. The primary behavior is front-loaded, and the entry-field detail earns its place by substituting for an absent output schema.

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?

The description is sufficient for a read-only list operation with well-documented parameters. It lists return entry fields, which matters because there is no output schema. It does not mention ordering or error cases, but these are minor given the simple scope and schema coverage.

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 parameters are already documented with defaults and semantics. The description adds no parameter-specific detail beyond what the schema provides, which is acceptable under the 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 uses a specific verb ('Return') and clearly names the resource: a paginated, base64-stripped slice of a capture's command list. It also enumerates the per-entry fields, so an agent can tell this is a command-list retrieval tool and distinguish it from capture summaries or validation tools.

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 establishes clear context: use it when you need command-list entries from a capture. It does not explicitly name alternatives or exclusion conditions, but the scope is specific enough that an agent can reasonably infer when to call it.

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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