get_kb_article
Fetch complete knowledge base article details from GLPI by providing the article ID.
Instructions
Retourne le detail complet d'un article de la base de connaissances.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| article_id | Yes |
Fetch complete knowledge base article details from GLPI by providing the article ID.
Retourne le detail complet d'un article de la base de connaissances.
| Name | Required | Description | Default |
|---|---|---|---|
| article_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries full responsibility for disclosing behavioral traits. It only says 'returns the complete detail' without addressing return format, error conditions, authentication needs, or whether the article must be visible/published. For a read operation, this is minimal disclosure but lacks any behavioral context beyond the basic action.
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, concise sentence in French (8 words). It is front-loaded with the action 'Retourne' and immediately specifies the object. There is no waste, and it is appropriately sized for the tool's simplicity.
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?
The tool is simple (1 parameter, no output schema, no annotations) and the description states the core purpose. However, it lacks context about what 'complete detail' includes, whether the article must be in a certain state, or any related sibling interactions. Given the low complexity, the description is minimally viable but leaves room for more details about return values and conditions.
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 has 1 parameter (article_id) with 0% description coverage. The description does not explicitly mention the parameter, but the phrase 'd'un article' implies that article_id identifies the article. Given that the parameter is a simple integer ID and its purpose is self-evident from the schema, the description provides marginal added meaning but does not fully compensate for the lack of schema description.
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 verb 'Retourne' (returns) and the resource 'le detail complet d'un article de la base de connaissances' (complete detail of a knowledge base article). It distinguishes itself from sibling tools like list_kb_articles and search_kb_articles by focusing on retrieving a single article's full detail.
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 provides no guidance on when to use this tool versus alternatives. It does not mention any exclusions, prerequisites, or context for choosing get_kb_article over search_kb_articles or list_kb_articles. The agent receives no usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/svtica/glpi-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server