query_python

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

The description discloses critical behavioral traits: it is an unsandboxed eval/exec in the server process, read-only by convention but not enforced, and output is capped. No annotations were provided, so the description fully covers the safety and execution model.

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 concise with four sentences, each adding value. It is front-loaded with verb and scope, and no extraneous information is present.

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?

Given the dangerous nature of the tool (unsandboxed eval), the description covers its purpose, usage guidelines, behavioral traits (safety, output cap), and disable mechanism. No output schema is provided, but output behavior is described. The description is complete for an agent to decide when and how to use it.

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 single parameter 'code' has no schema description (0% coverage), but the description adds meaning by explaining that the code is Python executed in a specific scope with raw bindings. This provides sufficient context for the agent to understand how to use the parameter.

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 identifies the tool as an 'escape hatch' for running Python against the live design, specifying the verb (run Python), resource (live design), and scope (bindings, session, top). It also distinguishes itself from sibling tools by instructing to prefer typed tools above and use this only for queries they cannot express.

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 explicitly states when to use this tool ('only for queries they cannot express') and when not to ('Prefer the typed tools above'). It also mentions that operators can disable it via an environment variable, providing clear guidance on appropriate usage.

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