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

Annotations already mark the tool as read-only and idempotent. The description adds behavioral details: deterministic integrity hashes, JSON-encoded nested tabular cells, and explicit rejection of ambiguous duplicate keys or non-finite numbers. These go beyond safety annotations and align with the declared non-destructive nature.

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 a single dense sentence that front-loads the action and formats. It packs many behavioral specifics but remains readable; no unnecessary words, though it could be broken into two sentences for readability.

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?

With an output schema present, the description covers the main conversion behavior, input formats, and edge-case handling. It omits only secondary details like the content length cap, which is in the schema. For a 4-parameter tool with rich annotations, this is sufficient.

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% (format, root_mode, and target_format are documented; content lacks a description). The description adds context on root_mode's 'preserve' behavior and format restrictions, but does not compensate for the undocumented content parameter or add syntax-level detail beyond the schema.

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 uses the specific verb 'Convert' and enumerates the exact formats (CSV, TSV, JSON, JSON Lines/NDJSON, YAML), plus optional root preservation and rejection of ambiguous input. This clearly differentiates it from sibling data tools like data.json-repair or data.clean.

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 use for format conversion but does not explicitly state when to prefer it over alternatives or mention exclusions, such as when to use data.json-repair for malformed input. No alternatives are named, so guidance is only implicit.

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