wait_python

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

No annotations provided, but description fully discloses behavioral traits: waiting does not interrupt execution, full output delivery for # loommux: --full-output, returns 'running' for incomplete full-output runs. Contradictions: none.

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?

Description is well-structured with sections but verbose (repeats schema defaults). Could be more concise by avoiding redundant parameter details. Every sentence adds value but length is suboptimal.

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?

Despite no output schema, description explains return behavior: on timeout returns running status, on completion returns status or full output. Covers edge cases like --full-output in running state. Complete for a wait 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?

Schema covers both parameters with full descriptions (default, type, behavior). Description mainly reiterates schema info without adding new meaning. Baseline 3 with 100% schema coverage is appropriate.

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 clearly states it waits for an execution to end or returns its current status on timeout, with specific verb '等待' and resource 'execution'. It distinguishes from siblings like interrupt_python and read_python_output by focusing on waiting behavior.

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?

Explicitly explains when to use this tool (wait for execution), mentions timeout only ends tool call not execution, and suggests alternatives like read_python_output or re-calling the tool. Selection rules reference sibling python_execution_status.

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