network_stats
Get Joy network statistics
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Get Joy network statistics
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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?
No annotations are present, so the description carries the full burden of behavioral disclosure. It does not state whether the operation is read-only, what data is included in 'statistics', or any limitations such as time ranges or aggregation methods. This is a significant gap for a tool that is otherwise opaque.
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 that front-loads the purpose without unnecessary words. It is appropriately sized for the tool's simplicity, though it sacrifices detail for brevity. It is not verbose but lacks substance to fully inform the agent.
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 absence of annotations, output schema, and detailed description, the tool is under-specified. It does not convey what network statistics are available, how they are formatted, or any expected response structure. For an agent to invoke this tool effectively, more context would be necessary.
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 tool has zero parameters, and the input schema shows an empty properties object. With no parameters to describe, the baseline of 4 applies. The description does not need to add parameter semantics, though it could mention that no inputs are required, which is already evident from 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 clearly identifies the tool as retrieving 'Joy network statistics' with a specific verb and resource. It is distinct from sibling tools like get_org_dashboard or get_wallet, which target different data types. However, it does not specify what kind of statistics are returned, preventing a perfect score.
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 is provided on when to use this tool versus alternatives. It does not mention exclusions, prerequisites, or contextual triggers. The tool simply states what it does without clarifying its use case among the sibling 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.
Most tools target distinct resources and actions. The only potential confusion is between approve_job and complete_deal, both releasing payments, but descriptions clearly differentiate job vs deal contexts. Overall, tools are well-separated.
Almost all tools follow a consistent verb_noun pattern (create_, get_, list_, etc.). The only outlier is network_stats, which lacks a verb, but this is a minor deviation from an otherwise uniform convention.
With 29 tools, the set exceeds the 25-tool threshold for a well-scoped server. While the platform covers many domains (jobs, payments, trust, identity, campaigns, tickets), the high count feels heavy and could benefit from consolidation or clearer separation into sub-modules.
Core job and stake lifecycles are fully covered, but tickets and campaigns only support create/list/get with no update, delete, or close operations. Payment also lacks a direct send/unified transfer option. These gaps are notable but workarounds exist via deals and top-up links.