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

Adds genuinely non-obvious behavior beyond the annotations: no credit spend, immediate availability for inline text, and background processing for blog_url — the last being critical since a follow-up create_article may run before the sample exists. It does not say how to tell when background processing finishes, which would have completed the picture.

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?

Four short sentences, front-loaded with purpose and the create_article linkage, then the cost and timing facts. Every sentence carries distinct information with no restatement of the name.

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 4-parameter write tool with no output schema, the description covers cost, timing, and the async path, which are the main risks. It omits whether repeated calls append or replace existing samples and what is returned, leaving a small but real gap for a non-idempotent tool.

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?

With 50% schema coverage, the description partially compensates by framing text and blog_url as two alternative input modes, reinforcing the schema's "Omit when using blog_url" note. However, it adds nothing about the undocumented title and author_id parameters, so half the surface remains explained only by bare types.

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 ("Add a writing sample to an author") and immediately names the downstream consumer (create_article), which separates it from siblings like add_chatbot_content and update_brain. An agent knows exactly what this tool produces without opening the schema.

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?

Gives clear usage context via the create_article dependency and distinguishes the two input modes (inline text vs blog URL). It stops short of naming when not to use it or which sibling to prefer for other content types, so it is clear context rather than explicit exclusions.

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