Get one article
get_articleMetadata + product list for one published article by slug. Fetch the markdown_url for the complete body text.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes |
get_articleMetadata + product list for one published article by slug. Fetch the markdown_url for the complete body text.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It informs the agent that the response includes metadata and a product list, not the full article body, and that the markdown_url must be fetched separately. This is valuable insight into the tool's behavior beyond what the schema or annotations supply, though it could have mentioned error cases like 'article not found.'
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 no wasted words. The first sentence front-loads the core purpose, and the second adds the essential detail about fetching the body. Perfectly scoped for a simple get-by-slug tool.
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 one-parameter read-only tool, the description covers the essential context: what you get (metadata + product list) and how to obtain the complete body (via markdown_url). It doesn't address pagination, error states, or authentication, but those are less critical given the tool's simplicity and the absence of an output schema.
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?
The schema provides no description for the 'slug' parameter (0% coverage), so the description must compensate. It does clarify that 'slug' identifies the article, which is helpful but minimal. The parameter is simple and self-explanatory, yet the description doesn't provide examples, format constraints, or note that the slug must be a published article. Adequate but not thorough.
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 a specific action ('Get one article'), the resource ('published article'), and the identifier ('by slug'). It also differentiates from siblings: get_product is for products and search_articles implies searching rather than direct fetch, making this tool's unique role obvious without looking at other tools.
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 implies when to use this tool—when you have a slug and want metadata plus a link to the full body. It doesn't explicitly mention alternatives like 'use search_articles to find articles by keyword,' but the phrase 'by slug' and the instruction to fetch the markdown_url indicate the intended flow. A clear context is provided, though explicit exclusions are missing.
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 targets a distinct resource and action: article, editorial set, product, vetting criteria, and search/list operations are clearly separated. No overlap in purpose; 'get' vs 'search' vs 'list' clear.
All tools follow a consistent verb_noun snake_case pattern (get_*, list_*, search_*), with clear verbs and nouns.
7 tools is well-scoped for a catalog server covering articles, products, and editorial sets. Each tool has a distinct role and none are redundant.
The surface covers search and retrieval for all core entities (articles, products, editorial sets) plus the vetting criteria. For a read-only public catalog, there are no apparent dead ends or missing operations.