listPostsList a site's posts or articles from its own API or feed.
WordPress, Substack, Squarespace and Discourse answer through their APIs;
anything else through RSS or Atom. Titles, URLs and dates — use `scrape`
on a URL to read one.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| limit | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds behavior beyond that: it explains how the tool selects API vs RSS/Atom based on the platform, what fields are returned, and directs the agent to scrape for full content. It omits pagination/rate-limit details, but for a read-only list tool this is a minor gap.
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?
The description is three sentences with no filler. The primary action is front-loaded, followed by platform-specific details and an alternative-tool pointer. Every sentence earns its place and the structure is easy to scan.
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-value details are not needed in the description. The description covers platform behavior, returned fields, and the next step via scrape. The only meaningful gap is the undocumented limit parameter, which prevents a perfect score. Overall, an agent can use this tool correctly with minimal ambiguity.
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 0% – neither url nor limit has any schema documentation. The description implies url is the site URL and mentions output fields, but it never explains limit (e.g., maximum number of posts) or the expected url format. With zero schema coverage, the description needed to carry this burden and does not.
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 and resource: 'List a site's posts or articles from its own API or feed.' It clearly distinguishes itself from sibling listProducts and from scrape by specifying the output fields (titles, URLs, dates) and pointing to scrape for reading one post. An agent can immediately identify what this tool does.
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 gives practical context for when to use the tool: WordPress, Substack, Squarespace, and Discourse go through APIs, while everything else uses RSS/Atom. It also explicitly names scrape as the alternative for reading a single post. It does not explicitly exclude other sibling tools, but the platform breakdown and the scrape pointer provide solid usage guidance.
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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