emailoctopus_list_campaignsList all campaigns in the account. Returns {data:[...],paging:{...}} — each campaign's id, name, status, subject, and created_at. Paginate with limit (max 100) and starting_after. EmailOctopus: GET /campaigns.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max campaigns to return (1..100). | |
| starting_after | No | Pagination cursor — the id to start after (from the previous page's paging). |
Changes observed during successful MCP inspections.
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the safety profile is covered; the description adds genuinely useful context beyond that by describing the response envelope ({data, paging}), the per-campaign fields, the 100-item cap, and the underlying API endpoint. It does not mention rate limits or total-count behavior, so it stops short of a 5.
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?
Three dense sentences with zero filler, front-loaded with purpose, then return shape, then pagination. Every clause carries information an agent can act on.
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?
With no output schema, the description correctly supplies the return structure and pagination contract, which is what an agent needs for a list endpoint. It is essentially complete, lacking only minor operational details such as ordering or rate-limit behavior.
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%, so both parameters are already documented in the schema; the description restates the same facts (max 100, cursor semantics) without adding new syntax or edge-case detail. Baseline 3 applies when the schema does the heavy lifting.
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 and resource ('List all campaigns in the account'), and the 'all' plus account scope distinguishes it from the single-resource sibling get_campaign. It does not name a sibling alternative explicitly, so it falls short of the 5 bar.
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?
Usage is implied rather than stated: the description shows how to paginate but never says when to choose this over get_campaign or the report tools. No exclusions or prerequisites are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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