ag_table_json_to_csv

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

With no annotations provided, the description carries the transparency burden. It discloses key behaviors: nested values are JSON-encoded, column order defaults to sorted union of keys, output includes a Guild-signed provenance envelope, and API key usage affects rate limits/budget. It does not describe failure modes or edge cases, but the main side effects and constraints are covered.

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 moderately detailed but not bloated. It uses short paragraphs and includes the embedded JSON schema, which is useful but adds length. Overall, every sentence contributes meaningful information about behavior, parameters, or output.

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?

The output schema is provided separately, and the description adds helpful context about the provenance envelope and return shape. It does not provide an example or explain every output field, but the combination of the prose description and the output schema gives an agent enough context to invoke and interpret the tool 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?

The description explicitly documents the payload schema with required 'rows' and optional 'columns', including constraints like minItems and maxItems for rows. It also explains the api_key parameter in the context of member budget usage. This goes well beyond the minimal input schema and gives clear meaning to both 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 clearly states the tool's purpose: 'Serialize an array of JSON objects to CSV' and further clarifies that row objects are converted with a stable, caller-controllable column order. It is easy to distinguish from sibling tools like ag_table_csv_to_json because the direction of conversion is explicit.

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 practical usage details: it mentions determinism, fixture verification, guest availability, rate limiting, and the effect of passing an api_key. It does not explicitly contrast with ag_table_csv_to_json or other table tools, but the purpose statement is clear enough that an agent can infer when to use it.

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