random_imageRandom image (optionally from a category).
| Name | Required | Description | Default |
|---|---|---|---|
| category | No |
| Name | Required | Description | Default |
|---|---|---|---|
| query | No | ||
| batchcomplete | No | Whether the query is complete |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {},
+ {
+ "category": "Category:Mountain landscapes"
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "batchcomplete": {
+ "description": "Whether the query is complete",
+ "type": "boolean"
+ },
+ "query": {
+ "properties": {
+ "categorymembers": {
+ "description": "Category members (when category specified)",
+ "items": {
+ "properties": {
+ "ns": {
+ "description": "Member namespace ID",
+ "type": "number"
+ },
+ "pageid": {
+ "description": "Member page ID",
+ "type": "number"
+ },
+ "title": {
+ "description": "Member title",
+ "type": "string"
+ },
+ "type": {
+ "description": "Type of category member",
+ "enum": [
+ "page",
+ "file",
+ "subcat"
+ ],
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "pages": {
+ "items": {
+ "properties": {
+ "imageinfo": {
+ "description": "Image information",
+ "items": {
+ "properties": {
+ "height": {
+ "description": "Image height in pixels",
+ "type": "number"
+ },
+ "mime": {
+ "description": "File MIME type",
+ "type": "string"
+ },
+ "size": {
+ "description": "File size in bytes",
+ "type": "number"
+ },
+ "url": {
+ "description": "File URL",
+ "type": "string"
+ },
+ "width": {
+ "description": "Image width in pixels",
+ "type": "number"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "ns": {
+ "description": "Namespace ID",
+ "type": "number"
+ },
+ "pageid": {
+ "description": "Page ID",
+ "type": "number"
+ },
+ "title": {
+ "description": "File title",
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ }
+ },
+ "type": "object"
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description claims 'random image' which suggests non-deterministic behavior, but the annotation idempotentHint=true contradicts this by implying the same input yields the same output. This contradiction undermines clarity.
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 that conveys the essential purpose without extraneous words. It is appropriately front-loaded and concise.
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?
Given the tool's simplicity and the presence of annotations and output schema, the description covers basic functionality. However, the contradiction with idempotentHint and lack of details about return format (though output schema exists) leave room for improvement.
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 description adds that the category parameter is optional and filters the image, which is not present in the schema (0% coverage). However, it does not specify valid category formats or provide examples beyond what appears in the schema's examples array.
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 tool retrieves a random image, optionally filtered by category. It distinguishes itself from sibling tools which are unrelated to images.
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?
No guidance on when to use this tool versus alternatives. The description implies its purpose but does not specify any conditions, exclusions, or related tools.
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.
Multiple tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical routers, and the six polymarket_* tools plus bet_research all cover prediction-market analysis with blurry boundaries. The server name 'Commons Wikimedia' also clashes with 30+ Pipeworx tools, making the overall purpose ambiguous. Only the handful of Commons-specific tools (category_members, file_info, file_revisions, random_image, search) are clearly distinct.
All names are lowercase snake_case and many follow a noun_phrase pattern (entity_profile, polymarket_edges, recent_changes), but verb styles are inconsistent: some are bare verbs (search, recall, subscribe), some are verb_noun (generate_llms_txt, resolve_entity, validate_claim), and several are noun-only (category_members, file_info, pipeworx_feedback). The style is readable but not predictable, mixing action-first and object-first conventions.
36 tools is far too many for a server ostensibly named 'Commons Wikimedia' — the vast majority belong to the Pipeworx data platform, not Wikimedia Commons. The count exceeds the 25-tool threshold for 'too many,' and the scope mismatch between the server name and the actual toolset makes the abundance feel even more unjustified.
For 'Commons Wikimedia,' the surface is severely incomplete: there is no upload, no category tree navigation, no file download, and no structured search beyond full-text. For the Pipeworx domain, coverage is broad but indirect — most data access funnels through aggregate/meta tools (ask_pipeworx, entity_profile, deep_research) rather than direct per-source tools, leaving gaps for granular lookups and leaving the Commons tools stranded with no real integration.