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list_stdlib_modules

Explore available PerfettoSQL standard library modules by domain (chrome, android, generic) with descriptions and usage examples. No trace needed.

Instructions

List a curated set of PerfettoSQL stdlib modules. Returns a JSON array — each entry has module (the value for INCLUDE PERFETTO MODULE), domain (chrome / android / generic), views, description, and an illustrative usage query.

Use when: exploring what's available before writing SQL against an unfamiliar trace type, or discovering modules outside the dedicated chrome_* tools (memory, sched, wattson, v8, etc.). Call this before load_trace if you want to scope your analysis upfront — no trace needs to be loaded.

Don't use for: discovering all stdlib modules — this is a curated subset of the most useful ones. The exhaustive list lives at https://perfetto.dev/docs/analysis/stdlib-docs.

Parameters: none.

Then use execute_sql with INCLUDE PERFETTO MODULE <module>; SELECT ... (both can be in one call). If PERFETTO_TP_PATH points to a custom binary, some modules may not exist in that version — verify column names with list_table_structure if a query fails.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

No annotations provided, but the description details return format (JSON array with fields), behavior with custom binaries, and suggests verifying columns if queries fail.

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?

Each sentence adds value, front-loaded with purpose and usage. Well-structured with clear sections (use when, don't use, parameters, follow-up).

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema or annotations, the description covers return structure, use cases, limitations, and edge cases (custom binary). Complete for a listing tool.

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

Parameters4/5

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

No parameters. Description notes 'Parameters: none.' Schema coverage is 100%. Baseline 4 because no parameters to document; description adds return format context.

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 the verb 'list' and the resource 'PerfettoSQL stdlib modules'. It distinguishes from siblings like list_tables and list_table_structure by focusing on modules.

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?

Explicitly states when to use ('exploring what's available', 'before load_trace') and when not to use ('don't use for discovering all stdlib modules'), with an alternative (the exhaustive list URL). Also provides follow-up steps.

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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