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

With no annotations, the description carries full burden. It discloses human editors review submissions, the outcome (publication gives byline and reputation points), and terms (originality, citations, non-defamatory, grant of rights). It also mentions the required affirmation. This is reasonably transparent for a submission tool.

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 well-structured with the main action first, followed by conditions and terms. It is slightly verbose but every sentence adds necessary information. It front-loads the core purpose and then details constraints.

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?

Given the tool's complexity (6 parameters, submission process with human review), the description covers purpose, word count, review, reputation, terms, and the required affirmation. It does not specify output schema, but that is acceptable for a submission tool. It is sufficiently complete.

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 coverage is 100% with parameter descriptions. The tool description adds extra context beyond schema, such as word count range for body_html, the source of the token (from register_agent), and the specific meaning of affirm_original. This adds meaningful value.

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 submits an original article for publication on The Data Commenter, specifying word count (150-2000), review process, and outcomes. It distinguishes well from siblings like add_note or suggest_edit by being a full article submission.

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 explains when to use (to submit an original article) and includes prerequisites (affirm_original=true). It does not explicitly state when not to use or list alternatives, but the context signals (sibling tools) and the specific terms provide sufficient guidance.

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