activityDaily transaction count (and UOPS where available) time series for an L2 project or all projects; accepts slug and range (7d/30d/90d/180d/1y/max, default 30d) from L2BEAT.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | No | Specific project (default: all) | |
| range | No | 7d | 30d | 90d | 180d | 1y | max (default 30d) |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "range": "7d",
+ "slug": "optimism"
+ },
+ {
+ "range": "max"
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "description": "Daily transaction counts and UOPS data",
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, etc., so the description's burden is lower. The description adds that the tool returns a time series from L2BEAT, but does not elaborate on error behavior, rate limits, or edge cases. This is acceptable given the annotations cover the safety profile.
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 is well-structured and front-loaded with the core purpose. Every word is necessary and adds information, with no superfluous content.
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?
For a simple tool with two optional parameters and an existing output schema, the description is complete. It describes what data is returned, the source, and the parameters. No additional information is needed for effective use.
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%, but the description adds default values for slug (all projects) and range (30d) not present in the schema. It also clarifies the range options (7d, 30d, etc.), adding value beyond the schema's property descriptions.
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 provides daily transaction count (and UOPS) time series for L2 projects, specifies the source (L2BEAT), and distinguishes from sibling tools focused on other domains. The verb 'get' is implied by the resource type.
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 explicitly lists accepted parameters (slug, range) and provides default values for range (30d). It implicitly guides usage by describing the data it returns, but does not explicitly state when to use vs. alternatives or when not to use.
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 tool set mixes L2beat-specific tools with a large number of unrelated Pipeworx, Polymarket, and other domain tools. While individual descriptions are clear, the overall set forces agents to navigate many irrelevant tools, causing confusion about the server's primary purpose.
Tool names follow inconsistent conventions: snake_case (list_projects), camelCase (ask_pipeworx), and mixed patterns (generate_llms_txt, bet_research). No unified naming pattern exists across the set, reducing predictability.
With 35 tools, the count is far too high for an L2beat server. Only about 5-6 tools are actually related to L2 scaling; the rest are from other domains, making the tool surface bloated and unfocused.
The L2beat-specific tools cover basic operations (list projects, get project, TVS, activity) but lack important features like bridge analysis, project comparisons, or detailed risk breakdowns. The numerous unrelated tools do not address gaps in L2 functionality.