confluence_list_spacesList all Confluence spaces in your instance. Returns space ID, key, name, type, and status. Use to discover documentation areas.
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | Filter by space type: "global" or "personal" | |
| limit | No | Number of spaces to return (default 25, max 100) |
| Name | Required | Description | Default |
|---|---|---|---|
| spaces | Yes | List of spaces in the instance |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "spaces": {
+ "description": "List of spaces in the instance",
+ "items": {
+ "type": "object"
+ },
+ "type": "array"
+ }
+ },
+ "required": [
+ "spaces"
+ ],
+ "type": "object"
+}Input schema / examplesAdded value: +[
+ {
+ "limit": 25
+ },
+ {
+ "limit": 50,
+ "type": "global"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint. The description adds the return fields but no additional behavioral traits beyond what annotations provide. With rich annotations, the description adds marginal value.
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 sentences, front-loaded with action, no wasted words. Every sentence adds value.
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 has an output schema, so return values are documented. The description mentions key fields. It lacks pagination or ordering details, but for a simple list tool with 0 required params, it is mostly complete.
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 coverage is 100%, and both parameters have descriptions in the schema. The description does not add new parameter information beyond stating return fields. Baseline 3 is appropriate.
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 it lists all Confluence spaces, specifies the returned fields (ID, key, name, type, status), and gives a usage hint ('discover documentation areas'). This distinguishes it from sibling tools like confluence_list_pages and confluence_search.
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 clearly states the tool lists all spaces and gives a usage hint. It does not explicitly mention when not to use it or name alternatives, but the context of sibling tools provides implicit differentiation.
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.
The set is dominated by near-overlapping research tools: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all answer factual questions with heavily overlapping descriptions, and the six polymarket_* tools plus bet_research form a second confused cluster. The five confluence_* tools are distinct, but an agent would struggle to pick among the research/betting alternatives without reading thousands of words of caveats.
Most names are snake_case, but the conventions are mixed: verb_noun (confluence_create_page, validate_claim), noun_verb (bet_research), prefixed nouns (polymarket_arbitrage, pipeworx_feedback), and bare verbs (recall, forget). The glaring issue is that the server is named Confluence yet only 5 of 36 tools carry the confluence_ prefix, leaving the other 31 tools with no thematic prefix and no consistent pattern.
36 tools is already in the 'too many' range, but the mismatch is deeper: only 5 tools relate to Confluence while 31 tools cover an entirely different domain (Pipeworx data research, prediction markets, subscriptions). For a wiki server this is wildly over-scoped; as a combined surface it is bloated and lacks a unifying purpose.
For the Confluence domain the surface is incomplete: pages can be created, fetched, listed, and searched, but there is no update_page, delete_page, comment, attachment, or content-type coverage, leaving obvious CRUD dead ends. For the Pipeworx domain, coverage is broad but disorganized, with overlapping research paths and no clear hierarchy.