schema_check

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

With no annotations, the description carries the full burden, and it does disclose one meaningful trait: it is local-only and never uploads user data. It does not say whether the tool is read-only, what happens on failure, or how results are reported, so the disclosure is real but thin.

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?

Two tight sentences, no filler, with the core purpose front-loaded and the locality guarantee immediately after. Every clause carries information.

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 four-parameter tool with no annotations and no output schema, the description covers purpose, type vocabulary and data locality, but leaves the relationship to validate_csv and the shape of the returned report unexplained. Adequate but with clear 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 description coverage is 75%, just under the high-coverage threshold, so the schema does most of the work. The description adds the closed type vocabulary for columnTypes, which is genuinely useful, but says nothing about delimiter behavior or how requiredColumns interacts with the type map.

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: checking required columns and column types, and even enumerates the supported type vocabulary. However, it never distinguishes itself from the sibling validate_csv, whose remit plausibly overlaps, so an agent cannot fully disambiguate from the name plus description alone.

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 only usage constraint is 'Local files only', which limits the input domain but says nothing about when to reach for this versus validate_csv or the other CSV siblings. No prerequisites, no when-not guidance.

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