base_analytics
Fetches Base 0x wallet balance and nonce stats ($0.002 USDC)
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes |
I used the same url for two different postings.
Fetches Base 0x wallet balance and nonce stats ($0.002 USDC)
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes |
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?
The description discloses a per-call cost ($0.002 USDC), which is useful behavioral information beyond the schema. However, with no annotations, it does not mention output format, error behavior, authentication requirements, or rate limits, leaving several behavioral details undisclosed.
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?
A single well-structured sentence conveys the core function and cost with no filler. The essential information is front-loaded, which is ideal for a simple one-parameter tool.
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 fetch tool, the description is adequate but not fully complete. It lacks an explanation of the return payload and any usage context relative to siblings, and there is no output schema to compensate.
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 description coverage is 0%, but the description partially compensates by implying the 'address' parameter is a Base 0x wallet address. It does not clarify the required address format or chain details explicitly, so the semantic guidance remains thin.
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 uses a specific verb ('Fetches') and names a precise resource: Base 0x wallet balance and nonce stats. This clearly differentiates the tool from siblings like web_scraper or pdf_extractor, which serve unrelated purposes.
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 about when to use this tool versus alternatives such as data_feeds or public_data_feed. The cost hint is present, but there is no explicit context for selection or exclusions.
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.
Several tools cluster around web content retrieval: web_scraper, browser_scraper, extract_json, and render_screenshot all pull from web pages and could be confused. data_feeds and public_data_feed also sound similar. Most other tools have distinct purposes, but these overlapping clusters create real selection ambiguity.
Tool names mix verb-led conventions like deploy_contract, extract_json, and render_screenshot with noun-led names like browser_scraper, pdf_extractor, and smart_contract_verifier. Pairs such as web_scraper vs browser_scraper and extract_json vs pdf_extractor are also stylistically inconsistent.
Twelve tools is a reasonable count for a paid gateway offering data extraction, feeds, and contract deployment. However, the scraping/extraction cluster is somewhat redundant, so the set could be tightened without losing much functionality.
The toolset broadly covers web data extraction, PDF processing, feeds, Base/Solana contract deployment, and blockchain analytics. Notable gaps include the lack of Solana-side balance/analytics tools and any post-deployment contract interaction or management capability.