get_articleRetrieve public metadata and the paid structured API URL for one article by slug. CMS-authorized clients may also request full Markdown directly from this tool.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | ||
| include_content | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, idempotentHint, and destructiveHint. The description adds value by explaining what is returned (metadata and a paid URL) and by disclosing the authorization nuance for full Markdown. No contradiction with the annotations.
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 concise sentences with the core purpose front-loaded and the optional capability stated second. Every word earns its place; no redundant or vague phrasing.
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 read-only, idempotent two-parameter retrieval tool, the description covers the main purpose, the key parameter, and the optional behavior, while annotations cover safety. It could be slightly stronger by explicitly naming sibling tools for routing or clarifying what 'paid structured API URL' entails, but nothing critical is missing.
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?
With 0% schema description coverage, the description partially compensates: 'by slug' explains the slug parameter, and 'request full Markdown' hints at include_content. However, it does not explicitly map include_content to the parameter or mention the default false, leaving some ambiguity for the agent.
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 clearly states the action (retrieve), the resource (public metadata and paid structured API URL), and the identifier (slug). It explicitly says 'for one article by slug,' which makes it distinguishable from the sibling list/search tools without ambiguity.
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 phrase 'for one article by slug' gives a clear main use case, and the note about CMS-authorized clients adds a conditional scenario. However, it never mentions alternatives like search_articles or when not to use this tool, so the guidance is clear but not exhaustive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: category browsing, article detail retrieval, latest article listing, search, and commission quote preparation. Even among the article tools, the retrieval modes are distinct enough that an agent would not easily confuse them.
Most tool names follow a readable pattern with 'articles' as a common noun and verbs like get, search, and prepare. Names like latest_articles and articles_by_category break the strict verb_noun convention, but the overall pattern remains predictable.
Five tools is a well-scoped size for a server that combines article research with commission quote preparation. Each tool covers a distinct need and none feel redundant or unnecessary.
Article discovery is well covered with search, category, latest, and detail retrieval, and the quote tool handles validation and endpoint preparation. Minor gaps exist, such as no explicit category listing endpoint and no follow-up execution/payment tool, but agents can work around these.