list_article_revisionsList article revision history (read-only audit trail). KnowledgeOwl API: GET /articlerevision.json. Returns { valid, page_stats, data:[...] }.
| Name | Required | Description | Default |
|---|---|---|---|
| _page | No | KnowledgeOwl pagination page number, 1-based. | |
| params | No | Additional documented query-string filters/operators to send verbatim (merged with the typed params above). |
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 already provide readOnlyHint=true, and the description reinforces this with 'read-only' and 'GET'. It adds useful behavioral context by naming the API endpoint and the response envelope { valid, page_stats, data }, which is beyond what the annotations alone supply. It does not discuss rate limits or pagination edge cases, but the annotation coverage lowers the burden.
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 compact and front-loaded: the first clause states the action, and the following fragments give the endpoint and return shape. Every sentence earns its place with no redundant filler.
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?
With no output schema, the description usefully includes the response structure. The schema handles parameter documentation. The main completeness gap is the lack of differentiation from list_article_versions and no mention of what the params object should contain for typical revision filtering.
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 description coverage is 100% for the two parameter slots (_page and params), so the baseline is 3. The description adds no parameter-level meaning: it does not clarify which filters are valid, whether an article identifier is expected, or how the params object should be structured beyond the schema.
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 and resource: 'List article revision history', and adds the clarifying context 'read-only audit trail'. It also exposes the exact KnowledgeOwl endpoint, which helps identification. However, it does not explicitly distinguish this tool from the nearly identical sibling 'list_article_versions'.
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 'read-only audit trail' implies when this tool is appropriate, and the endpoint reference adds concrete context. But there is no explicit guidance about when to prefer this tool over siblings like list_article_versions or list_articles, nor any exclusions or alternative routing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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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.