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

Annotations declare readOnlyHint=false and openWorldHint=true, so the agent already knows this is a non-idempotent creating submission. The description adds genuinely new context beyond that: reports are human-reviewed before publication and published entries credit the reporter, which sets expectations about latency and outcome.

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, zero filler. The most decision-relevant constraint (not yet in the library) is front-loaded, followed by what happens to the submission.

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 5-parameter creation tool with no output schema, the description covers the key workflow facts (not-listed prerequisite, human review, credit). It does not describe what the tool returns on submission, but the annotation profile makes that a minor gap.

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 100%, with per-field guidance (name example, credit, example snippet, whereSeen usefulness). The description adds no parameter-level detail beyond the schema, so the baseline 3 applies.

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 (report) and resource (AI design anti-pattern) with an explicit scope constraint — patterns NOT yet in the library. This cleanly separates it from get_pattern, list_patterns, and search_patterns.

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 a clear trigger: report when a design failure is seen repeatedly and a search of the library does not find it, which implicitly routes the agent to search_patterns first. No explicit 'do not use for X' clause, but the context is unambiguous.

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