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lpenguin
by lpenguin

get_capture_summary

Summarize a WebGPU capture to diagnose performance and correctness issues, providing object counts, command counts, shader entry points, validation errors, and heuristic findings.

Instructions

Summarize a capture: object counts by type, command counts by method, derived render statistics, shader entry points, validation error count, and heuristic performance/correctness issues. When the capture was taken with profilePasses:true it also includes gpuTiming (per-frame GPU time, slowest pass); when taken from a live page it includes frameBudget with a CPU/GPU/vsync bound verdict. For a focused performance report, use analyze_performance instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
captureIdNoCapture id (default: most recent).
includeIssuesNoInclude heuristic performance/correctness issues (default true).
includePassesNoInclude the per-pass breakdown (label, command range, draw/dispatch/bind counts) grouped by render/compute pass (default true).
includeMethodCountsNoInclude the per-method command counts map (default true).
Behavior4/5

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

No annotations are provided, so the description carries the behavioral burden. It discloses that output depends on capture configuration: profilePasses:true adds gpuTiming, and live-page captures add frameBudget. It also lists heuristic issue reporting. The read-only nature is implied by 'summarize' rather than explicitly stated, but there is no sign of mutation or side effects.

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 three dense sentences with no filler. The main purpose and result contents are front-loaded, the conditional additions are grouped logically, and the alternative tool is stated in the final sentence. Every sentence earns its place.

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?

With no output schema, the description does a good job enumerating what the summary will contain and which fields appear conditionally. Some terms like 'derived render statistics' are slightly vague, and it does not state whether the capture must already be loaded, but an agent has enough information to call the tool correctly with captureId and toggle flags.

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%, and each parameter is already well documented, including defaults and what toggling a boolean controls. The description adds broader output context but does not materially deepen the meaning of any specific parameter beyond what the schema already provides, so the baseline 3 applies.

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: 'Summarize a capture,' followed by a concrete list of what the summary contains. It clearly distinguishes itself from analyze_performance by naming that sibling explicitly, so an agent can tell this is the aggregate-summary tool rather than a focused performance tool.

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

Usage Guidelines5/5

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

The last sentence explicitly gives a when-not-to-use instruction: 'For a focused performance report, use analyze_performance instead.' It also explains conditional behavior for different capture sources, which helps the agent interpret results and decide when this tool is appropriate.

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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