get_articleFetch the full Markdown source of one article by its slug, as returned by search_articles.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Article slug, e.g. "ozempic-and-alcohol" | |
| locale | No | en |
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 mentions 'Fetch' which implies a read operation, but it doesn't mention potential errors, authentication, or the role of the locale parameter. The description is minimal and doesn't disclose any edge-case behavior.
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 a single sentence, 17 words, with no filler. It front-loads the action and object, making it immediately clear what the tool does.
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 simple 2-param tool, the description covers the primary parameter (slug) and return format (Markdown). However, it omits any explanation of the locale parameter and possible error cases. Given the absence of an output schema and annotations, this is not fully complete.
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 coverage is only 50%, with locale having no description in the schema. The description clarifies the slug parameter by stating 'by its slug', but it doesn't mention the locale parameter at all. Since the description should compensate for the low schema coverage, this is a gap.
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 uses the specific verb 'Fetch' and identifies the resource 'full Markdown source of one article' and the method 'by its slug'. It also references search_articles as the source of slugs, which distinguishes it from the sibling 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 phrase 'as returned by search_articles' provides clear context that this tool consumes slugs from search_articles, implying a workflow order. It doesn't explicitly exclude other tools, but the reference to a sibling tool gives useful guidance on when to use it.
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: calculate_reconstitution handles dosing math, search_articles finds blog posts, and get_article retrieves a specific article by slug. There is no overlap in functionality, so an agent can easily select the right tool.
All tool names follow a consistent verb_noun pattern with snake_case: calculate_reconstitution, get_article, search_articles. This makes the tool set predictable and easy to navigate.
Three tools is slightly small but appropriate for a niche server that combines a reconstitution calculator with blog content retrieval. Each tool serves a distinct purpose and none are redundant, though the set feels a bit minimal.
The calculator covers the core reconstitution math, and the blog tools allow searching and fetching articles. Minor gaps exist, such as no way to list all articles or handle other types of dosing calculations, but the surface is workable for the intended use case.