bnd_check

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 discloses the algorithm name and output format but does not reveal behavioral traits like side effects, authentication needs, rate limits, or whether the call is safe. This is insufficient for a potentially complex evaluation 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 two sentences with no filler or repetition. It front-loads the action and outputs, making it efficient for an AI agent to parse.

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 output schema and no annotations, the description explains the tool's core function and output but lacks details on parameter usage, prerequisites, error handling, or return value structure. It is minimally adequate but has gaps.

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 basic parameter descriptions. The description adds high-level output context (4D scores and decision) but does not explain how parameters like tags, confidence, or importance affect the evaluation or algorithm. Baseline 3 is appropriate because schema already documents parameters.

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 specifies a verb ('evaluate'), a resource ('content'), and a named algorithm ('3D Boundary balance algorithm'). It lists the exact output dimensions (TRJ/EVO/COG/BALANCE) and an accept/reject decision, distinguishing it clearly from sibling tools like bnd_stats or deduce.

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 the tool is for evaluating content via a specific algorithm, but it does not explicitly state when to use it versus alternatives (e.g., bnd_stats) or when not to use it. No exclusions or context are provided.

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