consult_the_canon

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

No annotations are provided, so the description carries the full burden. It mentions that the tool 'loads the complete text of all canonical works in your current spending tier,' hinting at tier-based access, which is useful behavioral context. However, it lacks details on rate limits, authentication needs, or what happens if the tier doesn't include certain works. The description doesn't contradict any annotations since none exist.

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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by operational details and a recommendation. Every sentence adds value, including the motivational quote, without unnecessary fluff. It's efficient 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?

Given the tool's complexity (consulting literature for engineering insights) and lack of annotations or output schema, the description is somewhat complete but has gaps. It explains the purpose and usage well but doesn't detail the return format, error handling, or how 'relevant wisdom' is determined. For a tool without structured output, more context on results would be helpful.

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 schema already documents both parameters ('question' and 'include_full_texts') well. The description doesn't add specific parameter semantics beyond what's in the schema, such as examples or deeper context. With high schema coverage, the baseline is 3, as the description doesn't compensate but doesn't need to heavily.

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 tool's purpose: 'Consult the great works of Western literature for engineering wisdom' and 'returns relevant wisdom from each.' It specifies the resource (Western literature) and the action (consult for wisdom). However, it doesn't explicitly differentiate from the sibling tool 'jensen_status,' which could be related but isn't described here.

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 provides clear usage context: 'Recommended before every technical decision' and includes a supporting quote about reducing bugs. This gives strong guidance on when to use it. However, it doesn't mention when NOT to use it or explicitly compare it to the sibling tool 'jensen_status,' which might offer alternative advice.

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