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

No annotations are provided, so the description carries the behavioral burden. 'List' and 'published campaigns' imply a non-destructive read that excludes unpublished items, which is useful, but there is no mention of permissions, pagination, result limits, or ordering — gaps that matter for a read that could return many rows.

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, zero filler, and the core scope ('published campaigns from DPYC') is front-loaded before the optional filtering note.

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?

An output schema exists, so return values need no explanation, and both parameters are fully documented in the schema. What remains thin is the behavioral envelope (pagination, auth) for an unannotated list operation, which keeps this from a 5.

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%, and both optional filters are documented in the schema with their own descriptions, so the baseline of 3 applies. The description restates the same two filters without adding format or identifier-syntax detail beyond 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 names a specific verb+resource ('List published pricing campaigns') and adds scope ('from the DPYC community'), so an agent immediately knows what this returns versus the singular sibling get_campaign. It does not explicitly contrast itself with any sibling, which keeps it short of a 5.

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?

'Optionally filter by operator or author npub' tells the agent the filters exist but not when to use them, when not to, or which sibling to prefer for a single campaign lookup. Usage is implied rather than stated.

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