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 does disclose a meaningful edge case — returns 0 when the matrix is missing or empty — which is genuine behavioral context. However it omits input format, how rows are delimited, and error behavior for malformed input.

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 front-loaded sentence delivers the operation and its fallback behavior with no wasted prose. The trial-call footer adds mild noise but is a standard pricing note rather than an impediment.

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 simple pure-computation tool with no output schema, the description adequately covers the return value and the missing/empty case. It falls short on the ambiguous dual parameter and the expected matrix input format, which an agent must know to call 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?

Two parameters (m and matrix) exist with 0% schema description coverage, and the description's 'matrix/m' notation hints they are interchangeable without confirming it or explaining the accepted format. An agent cannot tell which parameter to populate or how to encode the matrix.

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 and resource: returns the column count of a matrix, computed from the first row. It clearly contrasts with the sibling x402-matrix-rows, so an agent can distinguish the two. The only slight blur is the 'matrix/m' phrasing, which leaves it unclear whether those are aliases.

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 guidance on when to use this versus related matrix tools (rows, shape, is-square) or what input format is expected. The description only defines the operation itself, leaving the agent to infer all routing decisions.

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