get_articleFetch the full clean text of one article by its slug (the last path segment of an article URL).
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Article slug, e.g. "my-article-title" |
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| date | No | ||
| slug | Yes | ||
| text | No | ||
| title | Yes | ||
| summary | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "date": {
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "slug": {
+ "type": "string"
+ },
+ "summary": {
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "text": {
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "title": {
+ "type": "string"
+ },
+ "url": {
+ "type": "string"
+ }
+ },
+ "required": [
+ "slug",
+ "title",
+ "url"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is established. The description adds the useful behavior that it returns 'full clean text' and clarifies slug extraction from the URL, but does not go further into response details or edge cases; that is acceptable given the output schema.
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 with no filler. It front-loads the core purpose and includes the essential slug clarification in a parenthetical, making it easy to parse and remember.
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?
This is a simple one-parameter read-only tool with a full output schema and detailed annotations. The description plus schema provide everything an agent needs to call it correctly, including how to obtain the slug from an article URL.
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 input schema already documents 'slug' with an example, so baseline is 3. The description adds extra meaning by defining a slug as 'the last path segment of an article URL,' which helps the agent construct the correct parameter value from a URL.
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 ('fetch'), a specific resource ('one article'), and the identifying mechanism ('by its slug'). It clearly differentiates from sibling tools like list_recent_articles or search_articles, which operate over collections or use queries.
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 makes the usage context clear: use this tool when you want the full text of a specific article and have its slug. It does not explicitly mention alternatives or exclusions, but for such a focused single-resource tool the context is unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.