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

With no annotations, the description carries the full burden and does so thoroughly. It discloses determinism, fixture verification, guest rate limits, the option to pass an api_key for a member budget, and the inclusion of a provenance envelope. These are concrete behavioral traits beyond what annotations could provide.

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 front-loaded with purpose and usage, followed by concise behavioral notes and necessary schema details. Every sentence adds value; the embedded JSON Schema is justified because the tool's input schema is under-specified. No fluff or 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?

The tool has a rich description that covers what it does, when to use it, constraints (max input size, additionalProperties false), cost/auth behavior, and output format. Even with no annotations, an agent has enough context to invoke it correctly and understand the result.

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 input schema only shows an opaque 'payload' object, but the description compensates by embedding the exact JSON Schema for payload, including the required 'markdown' property, its maxLength, and the constraint on additional properties. It also explains the optional api_key parameter in context of rate limits. This is far beyond the schema alone.

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 starts with a specific verb+resource: 'Extract structured tables from markdown text.' It further specifies the exact input format ('GitHub-style pipe tables') and the output ('columns + rows per table'), which distinguishes it from sibling table tools like ag_table_csv_to_json and ag_table_json_to_csv.

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 gives clear usage context: 'Use on model output or docs before downstream structured processing.' It does not explicitly name alternatives or exclusions, but for this niche markdown-extraction tool, the intended scenario is clear enough.

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