chain stats
chain_statsBlock height + chain stats for Base or Ethereum. [price: $0.001/call USDC via x402]
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| chain | No | base (default), ethereum, or arbitrum |
ThirdMade Shelf
TDQS
B3.3/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry behavioral information on its own. It usefully discloses the per-call price and the general data returned, implying a read-only query, but it does not specify what 'chain stats' includes, the response format, or any rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The definition is extremely short, front-loaded with the core output, and uses a compact pricing bracket. Every element earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter read tool this is nearly adequate, but without annotations or an output schema the agent is left without a precise definition of 'chain stats' or the return payload. It also lacks usage context and the full set of supported chains.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents the single chain parameter and its default value. The description adds no new parameter semantics and even omits the schema-listed 'arbitrum' option.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description states a clear, specific resource: it returns block height and chain stats for Base or Ethereum, expanding on the name chain_stats. It does not explicitly differentiate from sibling tools, and it omits the schema-supported 'arbitrum' chain, which slightly muddies scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives like gas_now or other chain-related tools. Usage context is only implied by the tool's output; no conditions, exclusions, or sibling comparisons are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Try in Browser
Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
B3.2/5.0
Disambiguation3/5
Most tools have distinct purposes, but several clusters overlap: domain_facts, page_meta, and scrape all return page title information, and search_verify, hallucination_check, and sweep all target claim validation. The descriptions usually clarify the use case, but the boundaries are not always obvious.
Naming Consistency3/5
All names use lowercase snake_case, so there is a baseline consistency, but the pattern is mixed: bare verbs like scrape, summarize, and sweep sit alongside noun+noun forms like domain_facts and noun+verb forms like entity_find. The names are readable but do not form a predictable verb_noun API convention.
Tool Count3/5
At 26 tools, this is heavy and above the typical well-scoped 3-15 range, though the server is explicitly positioned as a broad shelf of paid utilities. Many tools are small one-purpose endpoints, so the count feels more like a catalog than a focused suite, but it is not an extreme mismatch.
Completeness4/5
The shelf covers the major advertised areas: web page analysis, research verification, text guards and NLP, blockchain reads, and image generation. There are some gaps such as no web search and no transaction sending, but agents can typically work around them or pair this with another server.