triangulation

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 states the tool solves a triangulation problem but doesn't describe how it behaves: e.g., what coordinate system is used, whether it returns a single position or multiple solutions, error handling, or assumptions (e.g., 2D vs. 3D). The description is too vague for a tool with no annotation coverage.

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 concise and front-loaded, with a clear main sentence followed by domain/category context. It avoids unnecessary words, though it could be more structured (e.g., separating purpose from domain). The single sentence efficiently conveys the core function without redundancy.

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 complexity (trigonometry application with 4 parameters), no annotations, no output schema, and 0% schema description coverage, the description is incomplete. It lacks details on parameter usage, behavioral traits, return values, and error conditions. For a tool that computes positions from distances, this leaves significant gaps for an AI agent to invoke it correctly.

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%, meaning none of the 4 parameters (point1, point2, distance1, distance2) are documented in the schema. The description adds no parameter information beyond the tool's general purpose. It doesn't explain what format 'point1' and 'point2' should be in (e.g., coordinates as strings), what units 'distance1' and 'distance2' use, or how they relate to the reference points.

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: 'Solve triangulation problem to find position from known distances to reference points.' It specifies the verb ('solve'), resource ('triangulation problem'), and outcome ('find position'), and includes domain/category context. However, it doesn't explicitly differentiate from sibling tools (mostly mathematical functions), though triangulation is distinct in purpose.

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 no guidance on when to use this tool versus alternatives. It mentions the domain ('trigonometry, Category: applications') but doesn't specify prerequisites, typical scenarios, or comparisons to other positioning methods. Without usage context, an agent might struggle to apply it appropriately.

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