model_scanner__list_patterns

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

With no annotations, the description carries the burden, and it does disclose the key trait: output is grouped by risk category, and the entries are the scanner's own red-flag definitions rather than a scan result. It does not say whether the list is static/complete or permission-gated, but for a zero-param read-only listing the remaining risk is small.

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?

A single sentence with no filler; the verb and the subject of the listing are front-loaded, with the pickled-model scope and the grouping qualifier following. Every clause adds information.

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?

For a zero-param, no-annotation, no-output-schema tool, the description covers what is returned (patterns grouped by risk category) and the context in which those patterns fire. It stops short of hinting at the per-entry fields, which the agent must discover from the response itself.

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 tool takes no parameters, so the baseline is 4 and there is nothing for the schema to compensate for. The description adds no parameter meaning because none exists.

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?

States a specific verb ('List') plus a precisely scoped resource ('dangerous Python global (module.function)'), and ties it to this scanner's domain ('referenced inside a pickled model file'). That domain framing clearly separates it from the many other *_list_patterns siblings (secret, prompt-leak, DNS, etc.).

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?

Usage is only implied: an agent can infer this is a reference/legend call and can be paired with model_scanner__scan_file or scan_directory, but the description never says when to call it versus scanning, nor names any alternative. No explicit exclusions or prerequisites are given.

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