NocturnusAI

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 effectively discloses key behavioral traits: it creates an independent copy (implying a write operation), specifies it's for hypothetical reasoning without modifying the main knowledge base (clarifying safety and intent), and mentions it copies 'all facts' (scope of operation). However, it doesn't cover aspects like error conditions, performance implications, or what happens if the target scope already exists.

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 action, followed by usage guidance and an analogy. Every sentence earns its place: the first defines the tool, the second explains when to use it, and the third provides a helpful comparison. It's efficient with zero waste.

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 no annotations and no output schema, the description does well by clearly explaining the tool's purpose, usage, and behavioral context. It covers the 'why' and 'when' effectively. However, it lacks details on return values or error handling, which would be needed for full completeness in a mutation tool without structured output.

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 adds value by explaining the overall purpose of forking (creating an independent copy for hypothetical reasoning), which provides context beyond the schema's parameter descriptions. It doesn't detail individual parameters but enhances understanding of their combined role.

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 ('Fork a knowledge base scope'), the resource ('creates an independent copy of all facts'), and distinguishes from siblings by explaining this is for hypothetical reasoning without modifying the main knowledge base. It uses the analogy 'Similar to git branch for knowledge' to enhance understanding.

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?

Explicitly states when to use this tool ('Use this for hypothetical reasoning... without modifying the main knowledge base') and provides a concrete example ('What if Alice moves to London?'). It distinguishes from potential alternatives by emphasizing the non-destructive nature for hypothetical scenarios.

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