SousChef

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the input and output types but lacks details on error handling, performance, or constraints (e.g., rate limits, authentication needs). The description does not contradict annotations, but it is insufficient for a mutation-like conversion tool.

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 front-loaded with the core purpose, followed by structured sections for Args and Returns. It is efficient with minimal waste, though the formatting could be slightly more streamlined (e.g., integrating the example directly into the main sentence).

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 tool has an output schema (Returns JSON string), the description does not need to detail return values. It covers the input parameter semantics adequately. However, for a conversion tool with no annotations, it could benefit from more behavioral context (e.g., transformation rules or limitations).

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 0%, so the description must compensate. It adds meaning by explaining the parameter 'search_query' with an example ('role:web AND environment:production'), clarifying its format beyond the schema's basic string type. With only one parameter, this provides adequate semantic context.

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 the specific action ('Convert') with precise resources ('Chef search query' to 'Ansible inventory patterns and groups'), distinguishing it from sibling tools like 'convert_chef_databag_to_vars' or 'generate_inventory_from_chef_environments' by focusing on search queries rather than databags or environments.

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 implies usage for converting Chef search queries to Ansible formats, but does not explicitly state when to use this tool versus alternatives like 'generate_awx_inventory_source_from_chef' or 'generate_dynamic_inventory_script'. It provides basic context without exclusions or detailed guidance.

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