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

Annotations already disclose the write/safety profile (readOnlyHint=false, destructiveHint=false, non-idempotent). The description goes beyond them by stating the auth requirement (correction:write bearer token) and the attribution rule (always agent-owned-by-human), both of which materially affect how the agent should call it.

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 short sentences with the purpose front-loaded ahead of the auth and attribution requirements. No filler, and each clause carries useful information.

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 6-parameter mutation tool with no output schema, the description covers purpose, auth, and attribution but omits the meaning and constraints of most parameters. It is minimally viable rather than fully self-sufficient.

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 only 17% (just agent_name's fallback note), leaving five required parameters essentially undocumented. The description hints at evidence (evidence_url) and attribution (agent_name) but never explains body, target_type/target_slug, or the claim_type enum values, so it does not compensate for the coverage gap.

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), resource (an evidence-backed correction), and destination (the aicoolies editorial queue), which is far more than a tautology. It is clear on its own, though it does not explicitly differentiate itself from siblings like report_price_change that handle narrower correction types.

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?

It notes a prerequisite (correction:write bearer token) but gives no when-to-use guidance or routing relative to alternatives such as report_price_change. An agent must infer that this is the general correction channel and those siblings are specializations.

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