robinx_statsFree coverage stats for RobinX: deployers scored, tokens indexed, real tokens, wallets flagged insider-linked, and serial-spam factories on Robinhood Chain (chain 4663).
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, destructiveHint=false, so the safety profile is clear. Description adds specific metrics returned but doesn't disclose additional behavioral traits (e.g., caching, rate limits, data freshness). It does not contradict annotations.
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?
Single sentence, front-loaded with 'Free coverage stats for RobinX', lists all metrics without redundancy. No wasted words.
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 no parameters, no output schema, and a simple purpose, the description covers essential information. It could mention output format or update frequency, but the lack is not critical for a straightforward stats tool.
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?
No parameters exist (empty input schema, 100% coverage). Description does not need to add parameter meaning. Baseline 4 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?
Description clearly states it provides 'coverage stats' for RobinX and lists specific metrics (deployers scored, tokens indexed, etc.). Verb is implicit but clear. Distinguishes from siblings like robinx_deployer or robinx_token by being a general stats endpoint.
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 explicit guidance on when to use this tool vs alternatives. It describes what it does but not the context (e.g., 'Use this to get an overview; for specific token details see robinx_token'). With many siblings, some usage advice would help.
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.
Each tool targets a distinct aspect of Robinhood Chain token analysis: deployer reputation, on-chain stats, social sentiment, wallet history, etc. Even overlapping concepts like verdict and report are clearly differentiated by scope and detail.
All tools follow a consistent 'robinx_<single_word_noun>' pattern, making it easy for an LLM to predict tool names and understand their purposes at a glance.
12 tools is optimal for a domain-specific server covering deployer analysis, token stats, social signals, wallet reputation, and composite reports. The count feels neither sparse nor bloated.
The tool set covers the core token analysis workflow: search, deployer check, on-chain stats, holder structure, social pulse, and comprehensive reports. Minor gaps like batch operations or historical comparisons exist but do not severely hinder usability.