de_bruijn

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

No annotations are provided, so the description carries the burden. It does disclose the defining output property (every k-ary substring appears exactly once), which is genuinely useful behavioral context, but says nothing about the output format, length, or handling of edge cases. A 3 reflects partial disclosure for an unannotated 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?

A single sentence, front-loaded with the verb and result, that defines the output mathematically. No filler.

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 two-parameter deterministic generator with fully documented parameters and no output schema, the definition is adequate: an agent knows exactly what it produces. A little more on the output representation (e.g., string vs array) would make it fully complete.

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 coverage is 100%, with both k and n already documented (alphabet size 2-10, substring length 1-10). The description's B(k,n) notation restates the roles but adds no meaning beyond the schema, so the baseline 3 is correct.

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 (Generate) and resource (de Bruijn sequence) and defines the output precisely as B(k,n) containing every k-ary substring of length n exactly once. It's clear what it produces, though it doesn't differentiate itself from neighboring combinatorics/math helpers like gray_code or necklace_count, which it doesn't need to since they compute different objects.

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?

No explicit when-to-use or when-not-to-use guidance, and no alternatives named. However, for a deterministic mathematical generator the usage is largely implied by the purpose, so this is minimally adequate rather than misleading.

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