ipython_complete

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

With no annotations provided, the description carries the full burden for behavioral disclosure. It adds useful detail about cursor handling ('cursor is taken to be at the end of the prefix') and the live namespace nature of the lookup, implying a read-only operation. However, it does not explicitly state that the tool is non-destructive, nor does it describe what happens on failure (e.g., empty completions) or whether results are returned as a list. These gaps prevent a higher score.

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?

Two sentences with no filler. The purpose is front-loaded, examples clarify usage immediately, and every clause contributes either to purpose, context, or a behavioral nuance. This is concise and well-structured.

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 being a simple two-parameter tool, the description omits critical information about the return value. Since there is no output schema, the agent must infer what the tool returns to use it correctly. The description does not mention whether completions are returned as a list, how errors are signaled, or any pagination/limit behavior. This makes the definition incomplete for an agent that needs to parse the response.

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 description coverage is 100%, so the baseline is 3. The description enriches the `prefix` parameter with examples and explains its interpretation, but it does not add information about the `name` parameter beyond the schema's 'Session to complete in.' The added value is modest, so a 3 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 begins with a specific verb ('Tab-complete') and resource ('partial expression against the session's live namespace'), followed by concrete examples (`df.gr`, `os.path.jo`). This clearly distinguishes it from sibling tools (run, start, etc.) and leaves no ambiguity about the tool's core function.

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?

The description states when to use it: 'Use this to discover attributes and names that actually exist before running code.' This implies a pre-execution exploration context and implicitly contrasts with running code (via `ipython_run`). However, it does not explicitly name alternatives or conditions to avoid using it, so it falls short of a strong 5.

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