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

No annotations are provided, so the description carries the burden. It discloses the auth requirement and the attribution behavior ('attribution is always agent-owned-by-human'), which is useful. However, it does not disclose what happens after submission (e.g., whether it's queued for review, whether it can be edited/withdrawn, or any side effects).

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?

Two sentences, no fluff, front-loaded with the action and resource. The credential requirement and attribution behavior are packed efficiently.

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 submission tool with 6 params and no output schema, the description covers the core purpose and auth but omits what happens after submission, whether the correction is immediately published or queued, and any constraints on evidence_url. It is adequate but not 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 description coverage is only 17%, so the description must compensate. It adds the evidence-backed requirement and the attribution fallback context, but it does not explain the meaning of target_type, target_slug, claim_type, or body beyond what the schema enums provide. The description adds some value but leaves most parameter semantics to 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 states a specific verb ('Submit'), a specific resource ('an evidence-backed correction to the aicoolies editorial queue'), and the required credential. It clearly distinguishes this from siblings like report_price_change or submit_run by naming the editorial queue and the evidence requirement.

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 when to use this tool: when submitting an evidence-backed correction to the editorial queue. It also states a prerequisite (correction:write bearer token). It does not explicitly name alternatives or exclusions, but the context is clear enough for an agent to select it over siblings.

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