extract_python_startup

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

All annotation hints are false and the description adds no behavioral disclosure: it does not say whether extraction mutates state, creates artifacts, requires a prior capture, or is safe to rerun. The description only lists output content, not operational behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no filler. Every word contributes to stating what evidence is extracted.

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

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

An output schema exists, which reduces the need to document return values. However, with dozens of sibling tools, no usage guidance, and no parameter detail, the description is adequate but not fully self-sufficient for an agent deciding whether and how to invoke this tool.

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

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

The sole parameter run_id is required, but schema description coverage is 0% and the description never mentions the parameter or its role. While 'run_id' is somewhat self-explanatory, the description does not add meaning such as scoping evidence to that run or expected value format.

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

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

The description names a specific verb ('Extract') and resource ('repeated startup, peak RSS, and package-grouped import evidence'), making the core purpose clear. It does not explicitly contrast with sibling extractors like extract_memray or extract_perfetto, so it stops short of full sibling differentiation.

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

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

There is no guidance about when to use this tool instead of the many sibling extraction/analysis tools. No prerequisites, exclusions, or decision criteria are stated, so the agent must infer usage entirely from the name and terse description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.