Get an article
get_articleFetch a single article by id. KnowledgeOwl API: GET /article/{id}.json. Returns { valid, data:{...} }.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The article id (a Mongo-style hex string). |
get_articleFetch a single article by id. KnowledgeOwl API: GET /article/{id}.json. Returns { valid, data:{...} }.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The article id (a Mongo-style hex string). |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, and the description adds useful behavioral context: it specifies the HTTP method (GET), the endpoint pattern, and the response envelope structure '{ valid, data:{...} }'. This goes beyond the annotations without contradicting them.
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 communicate the core action, the API endpoint, and the return shape without any filler. The most important information is front-loaded.
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 one-parameter read-only getter, the description is mostly complete. It mentions the response envelope, and the schema covers the parameter. It doesn't cover error cases or detailed data fields, but given the low complexity and the readOnlyHint, those are not critical gaps.
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 fully documents the single required parameter 'id' with a meaningful description ('a Mongo-style hex string'). The description merely repeats 'by id' and adds no new semantic detail beyond what the schema provides, so the baseline 3 applies.
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 ('a single article'), and the key selector ('by id'). It clearly distinguishes this from sibling tools like list_articles and list_article_revisions by emphasizing the single-record nature.
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 use case clear: retrieve one article when you have its id. It doesn't explicitly name alternatives or exclusion criteria, but the context is strong enough that an agent can infer this is the right tool for direct id-based lookup.
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 targeting a specific resource (article, category, glossary, etc.) and action (create, get, list, update). There is no ambiguity or overlap between tool names.
All tools follow a consistent verb_noun pattern: create_X, get_X, list_X, update_X. The exception 'knowledgeowl_request' is a utility escape hatch, clearly marked, and does not break the overall pattern.
At 24 tools, the set is slightly above the typical 3-15 range but still well-scoped for a knowledge base API covering many resources. Each tool serves a distinct purpose, and no tools are redundant.
The tool set lacks delete operations for all resources, and update operations are only available for articles and categories. Missing get tools for glossary terms, snippets, and other resources, though list tools are provided. This leaves significant gaps in lifecycle coverage.